Human pluripotent stem cell-based models for predictive developmental neural toxicity

ABSTRACT

The present invention relates to three-dimensional (3D) tissue constructs and methods of using such 3D tissue constructs to screen for neurotoxic agents. In particular, provided herein are methods of producing and using complex, highly uniform human tissue models comprising physiologically relevant human cells, where the tissue models have the degree of sample uniformity and reproducibility required for use in quantitative high-throughput screening applications.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims the benefit of U.S. Application Ser. No.62/098,803, filed Dec. 31, 2014, which is incorporated herein as if setforth in its entirety.

STATEMENT REGARDING FEDERALLY FUNDED RESEARCH OR DEVELOPMENT

This invention was made with government support under TR000506 awardedby the National Institutes of Health. The government has certain rightsin the invention.

BACKGROUND

Pluripotent stem cells offer a potentially powerful tool for improvingin vitro models and investigating the underlying mechanisms ofdevelopment of human neural tissue and of neurotoxicity. Animal modelshave provided insight into mechanisms of neurodevelopment, but are oflimited value for predicting developmental neurotoxicity due to poorlyunderstood differences in the human brain such as an expanded cerebralcortex. Thus, there remains a need for models that recapitulate complexhuman tissues and biological processes and that are suitable forscreening potentially hazardous compounds. Furthermore, there remains aneed in the art for efficient, reproducible, and xenogeneicmaterial-free methods for producing three-dimensional tissue constructsincluding neural tissue constructs having high uniformity forstandardized quantitative and qualitative assessments and for predictiveanalysis of candidate neurotoxic agents.

SUMMARY

In a first aspect, the present invention provides a method of producinga vascularized neural tissue construct. The method comprises or consistsessentially of (a) seeding a three-dimensional porous biomaterial withhuman neural progenitor cells; (b) culturing the seeded biomaterial fora length of time sufficient to detect differentiation of at least aportion of the neural progenitor cells; (c) dispersing on or within thecultured seeded biomaterial at least one human cell type selected fromthe group consisting of endothelial cells, mesenchymal cells, primitivemacrophages, and pericytes; and (d) culturing the seeded biomaterialcomprising the at least one dispersed human cell type under cultureconditions that promote cell differentiation, whereby a vascularizedneural tissue construct comprising human neurons and glial cells isproduced. The three-dimensional porous biomaterial can be a hydrogel.The hydrogel can comprise polymerized poly(ethylene glycol) (PEG) orpolymerized polysaccharide. The at least one dispersed human cell typecan be derived from a human pluripotent stem cell. The human pluripotentstem cell can be an embryonic stem cell or an induced pluripotent stemcell. In some cases, the at least one dispersed human cell typecomprises human pluripotent stem cell-derived primitive macrophages andthe 3D vascularized neural tissue construct further comprises maturemicroglia. Seeding the porous biomaterial can comprise contacting to theporous biomaterial at least one human neural progenitor cell.

In some cases, the method further comprises dispersing within or on theporous biomaterial a bioactive agent that modulates a morphologicalfeature, function, or differentiation status of a cell seeded ordispersed therein. The bioactive agent can be selected from the groupconsisting of a growth factor, a cytokine, and a bioactive peptide, or acombination thereof. The vascularized neural tissue construct canexhibit one or more properties selected from the group consisting of:(i) an interconnected vasculature; (ii) differentiated cells within theneural tissue construct mutually contact each other in three dimensions;(iii) more than one layer of cells; and (iv) a function or propertycharacteristic of human neural tissue in vivo or in situ. In some cases,the neurons and glial cells are selected from the group consisting ofGABAergic neurons, giutamatergic neurons, astrocytes, andoligodendrocytes. The porous biomaterial can be degradable. Thedegradable hydrogel can be selected from the group consisting of anenzymatically degradable hydrogel, a hydrolytically degradable hydrogel,or a photodegradable hydrogel. The enzymatically degradable hydrogel canbe matrix metalloproteinase (MMP)-degradable.

In another aspect, provided herein is a three-dimensional (3D)vascularized neural tissue construct obtained according to a methoddescribed herein. The neural tissue construct can comprise maturemicroglia. The neural tissue construct can comprise stratified layers ofneurons and glia.

In a further aspect, provided herein is a method of in vitro screeningof an agent. The method comprises or consists essentially of (a)contacting a test agent to a vascularized neural tissue constructobtained according to the method of claim 1; and (b) detecting an effectof the agent on one or more cell types within the contacted neuraltissue construct. The agent can be screened for toxicity to human neuraltissue. In some cases, detecting comprises detecting at least one effectof the agent on morphology or life span of cells or tissues within thecontacted tissue construct, whereby an agent that reduces the life spanof the cells or tissues or has a negative impact on the morphology ofthe cells or tissues is identified as toxic to human neural tissue. Insome cases, detecting comprises performing a method selected from thegroup consisting of RNA sequencing, gene expression profiling,transcriptome analysis, metabolome analysis, detecting reporter orsensor, protein expression profiling, Førster resonance energy transfer(FRET), metabolic profiling, and microdialysis. The agent can bescreened for an effect on gene expression, and detecting can compriseassaying for differential gene expression relative an uncontacted tissueconstruct.

In some cases, the method further comprises using a predictive model todetermine the relationship of gene expression levels of a panel ofmarkers for the test compound-contacted tissue construct to geneexpression levels of markers that are characteristic of exposure to aneurotoxic agent, where the predictive model is constructed usingtranscription and metabolic profiles obtained for each component of apanel of agents having known neurotoxic effects as markers of toxicityto human neural tissue.

In another aspect, provided herein is a tissue construct screeningsystem. The system comprises or consists essentially of an analyticaldevice configured to obtain data comprising measurements from a humanvascularized neural tissue construct; a computer controller configuredto receive the data from the analytical device; and a machine-basedadaptive learning system trained using known gene expression data andconfigured to select a subset of features from the data using a featureselection algorithm, where the subset of features correspond to a changein a level of expression of at least one gene following exposure to aknown or unknown compound. The human vascularized neural tissueconstruct can be obtained according to a method described herein.Measurements can comprise gene expression data obtained from microarrayanalysis.

In yet another aspect, provided herein is use of a three-dimensionalhuman vascularized neural tissue construct obtained according to amethod described herein in a drug discovery or toxicity screen.

These and other features, objects, and advantages of the presentinvention will become better understood from the description thatfollows. In the description, reference is made to the accompanyingdrawings, which form a part hereof and in which there is shown by way ofillustration, not limitation, embodiments of the invention. Thedescription of preferred embodiments is not intended to limit theinvention to cover all modifications, equivalents and alternatives.Reference should therefore be made to the claims recited herein forinterpreting the scope of the invention.

INCORPORATION BY REFERENCE

All publications, patents, and patent applications mentioned in thisspecification are herein incorporated by reference to the same extent asif each individual publication, patent, and patent application wasspecifically and individually indicated to be incorporated by reference.

This application includes a sequence listing in computer readable form(a “txt” file) that is submitted herewith. This sequence listing isincorporated by reference herein.

BRIEF DESCRIPTION OF THE DRAWINGS

This patent or application file contains at least one drawing executedin color. Copies of this patent or patent application publication withcolor drawing(s) will be provided by the Office upon request and paymentof the necessary fee.

The present invention will be better understood and features, aspectsand advantages other than those set forth above will become apparentwhen consideration is given to the following detailed descriptionthereof. Such detailed description makes reference to the followingdrawings, wherein:

FIGS. 1A-1B present (A) a schematic representation of a strategy forassembling a hydrogel tissue construct. In (A), the upper timelineincludes the differentiation protocols for obtaining neural progenitorcells (NPCs) from pluripotent stem cells, while the lower timelinereflects initial formation of tissue construct. Presented in (B) is aschematic representation of the chemistry of hydrogel formation bythiol-ene photopolymerization.

FIGS. 2A-2D are images demonstrating morphological characteristics ofneural constructs. Human embryonic stem cell-derived precursor cellswere co-cultured on polyethylene glycol (PEG) hydrogels in 24-wellTranswell inserts. Neural progenitor cells (NPCs) were seeded onsynthetic PEG hydrogels (day 0), followed by endothelial cells (ECs) andmesenchymal stem cells (MSCs) at day 9 and microglia/macrophageprecursors (MGs) at day 13. (A and B) Maximum projection Z stack (525-μmthickness) and slice views (NIS Elements) illustrating βIII-tubulin(green), GFAP (red), and DAPI (blue) for a day 21 neural construct. XZand YZ cross-sections are illustrated in the regions indicated by dashedlines. The boxed region in A is illustrated in B. (C and D) Volume viewimages (NIS Elements) corresponding to (C) the full neural constructshown in A (6,300 μm×6,300 μm×550 μm) and (D) the region shown in B(1,570 μm×2,290 μm×300 μm). (Scale bar in A, 1,000 μm and B, 500 μm.).

FIGS. 3A-3I are images (A-H) and a graph (I) demonstrating that tunablebiophysical and biochemical properties of thiol-ene hydrogels guide cellfunction. FIGS. 2A-2D demonstrates the influence of hydrogel propertieson spreading for mesenchymal stem cells (MSCs) cultured in PEG hydrogelsformed via thiol-ene photopolymerization. The images in FIGS. 2A-2Dillustrate PEG hydrogels that incorporate CRGDS for cellular adhesionand MMP-crosslinking peptides that are derived from a native collagensequence (ALA) or which have been engineered to enhance degradation rate(TRYP and LEU). Matrix remodeling can be tuned by controlling biologicalproperties of the synthetic matrix. Mesenchymal stem cell (MSC)spreading is a function of degradation rate and adhesion ligand density.MSC attachment and spreading was tuned by varying adhesion liganddensity (using the fibronectin mimic CRGDS) or the susceptibility of thecrosslinker to proteolytic degradation (by varying the P′₂ position ofthe amino acid sequence). (A) MSC spreading was maximized withTryptophan in the P′₂ position of the amino acid sequence and 1000 mMRGD. (B) MSCs remained rounded in hydrogels with the most degradablecrosslinker (Tryptophan in the P′₂ position), but without activeadhesion peptide (0 RGD condition, RGD replaced with non-bioactive RDGscrambled peptide). (C) Only limited spreading was observed whenTryptophan was replaced with Ala due to lower susceptibility to MMPdegradation while (D) intermediate spreading was observed whenTryptophan was replaced with Leu. (E, F) Live/dead staining demonstratesthat human umbilical vein endothelial cells (HUVECs) are viable whengrown in 3D synthetic extracellular matrices with two different RGDconcentrations which leads to differences in 3D organization. (G) Imagesof human dermal fibroblasts grown in 3D synthetic matrix compared to (H)collagen reveal that basic cell morphologies and cytoskeletal structureare indistinguishable between them (where gels are matched formechanical properties). (I) Modulus (stiffness) can be varied across awide range of values by choice of monomer density (wt %), molecularweight, and PEG backbone molecule (4-arm or 8-arm).

FIGS. 4A-4K are confocal images demonstrating that neural tissueconstructs are characterized by neurons with diverse morphologies andlong-range order. Immunofluorescence imaging reveals neuronal and glialphenotypes. (A-E) Maximum projection immunofluorescence imagesillustrating βIII-tubulin (green) and DAPI (blue) expression for fullvascularized neural construct formed within a 24-well transwell insert(top left). (F-J) Distinct neuronal phenotypes. (F) Calretinin (green)and Reelin (red). (G-K) βIII-tubulin (red) coexpressed with (G) GABA,(H) VGLUT2, (I) FOXG1, (J) Ctip2, and (K) Brn2. Scale bars: 100 μm(F-K).

FIGS. 5A-5D demonstrate vascular network formation within neuralconstructs. (A and B) Immunofluorescence for endothelial cells (CD31,green), glial cells (GFAP, red), and nuclei (DAPI, blue) for a day 21neural construct. (B) Zoom of the boxed region shown in A to illustrateassociation and alignment for a capillary tubule and radially orientedglial cells (arrows). The cells in B are shown as single channelgrayscale images for (C) CD31 and (D) GFAP. Scale bars in A, 250 μm andB-D, 100 μm (shown in B).

FIGS. 6A-6B demonstrate incorporation of microglia into neuralconstructs. (A) Gene expression for neural constructs with or withoutmicroglia (Quality Control Experiments; N.D., not detected). Statisticalanalysis was conducted using a Student's t test (TPM±SD; ***P<0.001; n=4replicate samples each). (B) Immunofluorescence images showing Iba1(microglia, red) and CD31 (endothelial cells, green) expression for aday 21 neural construct. Microglia adopt ramified morphologies (e.g.,closed arrow) and associate with capillary tubules (e.g., open arrows).(Inset) Iba1 (red) and DAPI (blue) expression for the cell pointed outby the closed arrow (Bottom, Right corner) and surrounding nuclei. Imageis brightened for clarity. (Scale bar, 100 μm.)

FIGS. 7A-7C demonstrate that neuronal tissue constructs exhibitstratified layers and radial organization of neuronal and glial cells.Maximum projection Z-stacks show immunofluorescence for neuronal(βIII-tubulin, green), glial (GFAP, red), and nuclear (DAPI, blue)markers. (A) Full neuronal construct at day 9 after NPCs were seededonto an MMP-degradable PEG hydrogel. Endothelial cells and mesenchymalsupport cells were added for full tissue constructs at day 9 to mimicrecruitment by neuroepithelial cells within the neural tube. (B, C)Higher magnification images illustrating stratification and radialorientation of early neuronal and glial populations. Scale bar=250 μm.

FIG. 8 is a table of gene expression data for 3D vascularized neuralconstructs.

FIG. 9 is a table providing Spearman's correlation data for replicateneuronal constructs formed with or without microglia on days 14 and 21.

FIGS. 10A-10E present machine learning predictions. (A) A linear supportvector machine (SVM) for a 2D problem, where an (n−1)-dimensionalhyperplane reduces to a line that separates the classes (filled vs. opencircles) and maximizes the closest points between classes (the supportvectors, which fix the position and orientation of the hyperplane). Thex_(i)s are the examples (points in A), the y_(i)s are their labels(filled or open in A), and w is the weight vector, or vector ofcoefficients on the features (the dimensions). The linear SVM's outputis the weight vector w and the other coefficient b. To make aprediction, the SVM computes the number w′x_(i)−b, and outputs the label0 (nontoxic, for our application) if this number is less than 0, and 1otherwise. The extensions required for the soft margin version of theSVM are highlighted in pink in the equation, which minimizes the sum ofthe distances between incorrectly classified training points (ξi) inaddition to the margin, and is used when the data are not linearlyseparable (Hall M, et al. (2009) The WEKA data mining software: anupdate. SIGKDD Explor Newsl. 11(1):10-18). (B) Performance data(averaged from day 16 (2-day dosing) and day 21 (7-day dosing) are shownin the form of receiver operating characteristic (ROC) curves. The ROCcurve plots true positive rate on the y axis against the false positiverate (1-specificity) on the x axis as the threshold is varied. FIGS.10C-10E present additional receiver operating characteristic (ROC) curveplots and toxins tested (E).

DETAILED DESCRIPTION

Previous in vitro studies have demonstrated the capacity for humanpluripotent stem cell-derived neural progenitor cells to self-assembleinto layered neuronal tissues that resemble the neocortex (Lancaster etal., Nature 501:373 (2013); Kadoshima et al., Proc. Natl. Acad. Sci.U.S.A 110:20284 (2013); Mariani et al., Proceedings of the NationalAcademy of Sciences 109:12770 (2012); Eiraku et al., Cell Stem Cell3:519 (2008)), which may be particularly relevant to developmentalneurotoxicity screening. However, prior neuronal tissue models lackedcritical components of the developing brain such as blood vessels andmicroglia. The present invention is based at least in part on theInventors' discovery that human pluripotent stem cell-derived precursorcells cultured in materials that are permissive towards remodeling formhighly uniform 3D vascularized neuronal tissues that recapitulate thecomplexity and organization of human tissues. The Inventors furtherdiscovered that the 3D vascularized tissues are useful for screeningcompounds and, using global gene expression profiles from the tissues,developed a machine learning protocol that correctly classified greaterthan 90% of test compounds. While it was known that human pluripotentstem cell-derived neuronal tissues provide an alternative to animaltesting for modeling human brain development, the Inventors' discoveredthat it was possible to produce complex human tissue models comprisingphysiologically relevant human cells and having the high sampleuniformity necessary for large-scale, quantitative enhanced throughputscreening applications.

Successful strategies to produce in vitro “organoid” models have beenreported for a variety of tissues (Ader & Tanaka, Curr. Opin. Cell Biol.31:23 (2014)), but Matrigel and/or suspension culture techniquestypically used for these procedures introduce variability that is notwell-suited for enhanced throughput quantitative analysis (Singec, Nat.Methods 3:801 (2006)). Accordingly, the present invention relates tocompositions including three-dimensional tissue constructs and organoidsobtained using monolayer culture techniques to assemble precursor cellson chemically-defined bioactive substrates. The present invention alsoprovides methods of using three-dimensional tissue constructs andorganoids as highly uniform models of human tissue and for screeningpotentially toxic agents. Among the advantages offered by the presentinvention, three-dimensional tissue constructs and organoids of theinvention provide biologically-relevant information about the effects ofvarious neurotoxic agents within the complex environment of neuraltissue. In addition, the present invention is useful for identifyingmaterials and combinatorial strategies for human tissue engineering.

Compositions

Accordingly, the present invention provides a composition comprising athree-dimensional (3D) tissue construct. As used herein, the term“tissue construct” refers to engineered tissues produced in vitro thatcomprise complex topologies and geometries (e.g., multi-layeredstructures, segments, sheets, tubes, sacs). The complex topologies andgeometries of the tissue constructs recapitulate cell-to-cellinteractions found within native tissues. As used herein, the term“three dimensional (3D) tissue construct” refers to an engineeredassemblage of cells and materials that forms a three-dimensional,interconnected complex structure to mimic in vivo physiologicalconditions. By contrast, two dimensional cultures comprise cellscultivated in a single layer in a tissue culture dish. An engineeredtissue construct of the invention comprises at least two layerscomprising a homogeneous or heterogeneous population of cells, whereinone layer of the tissue construct is compositionally or architecturallydistinct from another layer. In some cases, layers of the tissueconstruct comprise multiple cell types in spatially-defined positionsrelative to each other to recapitulate intercellular interactions foundwithin native tissues. In exemplary embodiments, the tissue construct isa 3D neural tissue construct that provides a microenvironment permissiveto in vitro development, in three dimensions, to recapitulate neuraltissue in vivo. A 3D neural tissue construct of the present invention isformed in vitro by the addition of neural progenitor cells to layeredtissue comprising neural and glial cell populations. An exemplaryembodiment is depicted in FIGS. 1A-1B. According to this embodiment, avascularized neural tissue construct is obtained by embedding humanES/iPS cell-derived endothelial cells, pericytes, and primitivemacrophages (microglial precursors) into a tunable hydrogel displayingspecific peptide motifs that promote capillary network formation. Tothis mesenchymal cell layer, neural and astrocyte precursors areoverlayed. The hydrogel is then cultured for about two weeks to form avascularized neural tissue construct that mimics in vivo cephalicmesenchyme-neural epithelial interactions. Neural progenitor cells(NPCs) and/or components derived from such progenitors are introduced byadding the components to the top of a three-dimensional tissueconstruct.

In some cases, the 3D neural tissue construct comprises layered neuraltissue lacking either vasculature or microglia. In other cases, a 3Dneural tissue construct of the invention further comprises vascularand/or microglia components. For example, a 3D neural tissue constructcan comprise stratified, vascularized neural epithelium, with or withoutmicroglia. Preferably, a 3D vascularized neural tissue construct asdescribed herein has at least one of the following properties: (i)interconnected vasculature; (ii) differentiated cells within the neuraltissue construct mutually contact in three dimensions; (iii) having morethan one layer of cells; and (iv) demonstrate a function or propertycharacteristic of human neural tissue in vivo or in situ.

In some cases, a composition of the present invention comprises athree-dimensional cortical tissue construct. In such cases, a 3Dcortical tissue construct comprises complex tissues that recapitulatethe structural organization and vascularization of human cerebralcortex.

Naturally derived ECMs used for three-dimensional culture (e.g.,Matrigel® (BD Biosciences, Bedford, Mass.), collagen gels) are notwell-defined, and typically expose cells to a wide variety of signalingfactors simultaneously. In order to optimize the influence of aparticular type of signal on cell behavior, without interference fromnumerous other signals acting in concert, alternatives to naturallyderived ECMs are preferred. In exemplary embodiments, a 3D tissueconstruct of the present invention comprises a porous biomaterial suchas a hydrogel. The term “hydrogel” refers to a highly hydrated porousmaterial comprising synthetic or biological components formed when anorganic polymer (natural or synthetic) is cross-linked via covalent,ionic, or hydrogen bonds to create a 3D open-lattice structure thatentraps water molecules to form a gel. Hydrogels appropriate forconstructing 3D tissue constructs of the present invention include,without limitation, synthetic hydrogels, bioactive hydrogels,biocompatible hydrogels, cytocompatible hydrogels, chemically definedhydrogels, chemically-defined synthetic hydrogels, and proteolyticallydegradable hydrogels.

As used herein, “bioactive” is intended to indicate the ability tofacilitate a cellular or tissue response, such as differentiation of apluripotent stem cell, induction of vasculogenesis, neural stem celldifferentiation, promotion of cellular attachment, promotion of cellself-assembly, and promotion of cell-cell interactions.

As used herein, the term “biocompatible” refers to the ability of apolymer or hydrogel to perform as a substrate that will support cellularactivity, including the facilitation of molecular and mechanicalsignaling systems, in order to permit proper cell self-assembly orcellular function such as tissue formation, production of solublebioactive molecules (e.g., growth factors), specific cell behaviors suchas migration and proliferation. In some cases, “biocompatibility” meansthe absence of components having cell- or tissue-damaging effects. Asused herein, the term “chemically defined” means that the identity andquantity of each component of a composition (e.g., a hydrogel) is known.An important goal in the fields of pluripotent stem cell culture anddirected differentiation of pluripotent stem cells is to develop culturematerials and culture media that provide improved performanceconsistency and reproducibility. In some cases, a chemically definedhydrogel for use in a neural tissue construct provided herein comprisesa minimal number of defined components/ingredients.

As used herein, the term “cytocompatible” means the hydrogel material issubstantially non-cytotoxic and produces no, or essentially no,cytotoxic degradation products.

As used herein, the term “proteolytically degradable” means that thecrosslinked backbone can be cleaved enzymatically or non-enzymaticallyto break down the scaffold network.

In some embodiments, a hydrogel appropriate for inclusion in a neuraltissue construct as described herein is at least partially containedwithin a three-dimensional structural framework. Preferably, astructural framework comprises a three dimensional structure preparedfrom one or more polymeric materials, including biopolymers.

A hydrogel appropriate for use in a neural tissue construct of theinvention can be prepared using various polymers including, withoutlimitation, poly(ethylene glycol) (PEG), polyvinyl alcohol (PVA),polyvinyl pyrrolidone (PVP), polyacrylamides, and polysaccharides. PEGis a polymer having solubility in water and in many organic solventsand, generally, lacking toxicity, antigenicity, or immunogenicity. PEGcan be activated at each terminus to be bifunctional. In other cases,one terminus can be modified to have a reactive moiety. For example, aPEG monomer can be modified to have a relatively inert methoxy moiety(e.g., methoxy-PEG-OH) at one terminus while the other terminus is ahydroxyl group that is readily chemically modifiable. Polysaccharidehydrogels are made by crosslinking natural or semi-syntheticpolysaccharides such as alginate, carboxymethylcellulose, hyaluronicacid, and chitosan. The cross-linking reaction allows for the formationof a three-dimensional network made of covalent bonds between thepolymer chains—a network that is stable under physiological conditions.

In some embodiments, a hydrogel appropriate for inclusion in a neuraltissue construct as described herein is at least partially containedwithin a three-dimensional structural framework. Preferably, astructural framework comprises a three dimensional structure preparedfrom one or more polymeric materials, including biopolymers. In otherembodiments, it may be useful for the bioactive hydrogel matrix to haveadditional structure or strength in the absence of a framework oradditives. In such cases, a bioactive hydrogel matrix is in astabilized, crosslinked form.

In exemplary embodiments, hydrogels (e.g., PEG hydrogels, polysaccharidehydrogels) are used to produce 3D tissue constructs of the invention.Cells can be readily encapsulated within these gels usingphoto-polymerization. See Fairbanks et al., Adv. Mater. 21:5005-5010(2009). Proteins and cells exhibit little to no intrinsic adhesion orinteraction with PEG hydrogels. See Drury & Mooney, Biomaterials24(24):4337-51 (2003); Nguyen & West, Biomaterials 23(22):4307-14(2002); and Hoffman, Adv. Drug Deliv. Rev. 54(1):3-12 (2002). Thus, PEGprovides an ideal “blank slate” upon which one can present specificbiological molecules to cells in a controlled manner.

To promote self-assembly of an engineered neural construct thatrecapitulates vascularized neural epithelium, it is advantageous to usea photo-polymerization strategy that uses “thiol-ene” chemistry. SeeFairbanks et al., Adv. Mater. 21:5005-5010 (2009). Step-growth thiol-enephotopolymerization is based on a reaction between a thiol and a vinylgroup in the presence of a photoinitiator—a reaction that results in ahomogeneous, cytocompatible hydrogel. Photopolymerization kinetics canbe controlled by altering the concentration of photoinitiator (e.g.,radical).

In some cases, a 3D neural tissue construct of the present inventioncomprises a hydrogel formed using PEG monomers functionalized withnorbornene. For example, a 3D neural tissue construct of the presentinvention can be prepared using a hydrogel comprising a 4-arm or 8-armPEG monomers reacted with 5-norbornene-2-carboxylic acid to form anorbornene-functionalized PEG solution.

In some cases, a hydrogel appropriate for neural tissue constructsdescribed herein comprise a bioactive agent such as a growth factor, acytokine, a bioactive polypeptide or peptide (e.g., RGD-containingpeptides), or any other bioactive ligand capable of interacting with abiomolecule of the cells cultured on or within the hydrogel. Peptidescomprising the fibronectin-derived RGD peptide sequence include, withoutlimitation, RGDS (SEQ ID NO:7), CRGDS (SEQ ID NO:2), Ac-CRGDS (SEQ IDNO:11); CRGDS-CONH(2) (SEQ ID NO:12), Ac-CRGDS-CONH(2) (SEQ ID NO:13),RGDSC (SEQ ID NO:8), CCRGDS (SEQ ID NO:9), and CCCRGD (SEQ ID NO:10).The number and type of appropriate bioactive agents for the presentinvention will depend on the types of cells cultured on the hydrogel.Examples of suitable bioactive ligands include, without limitation,carboxyl, amine, phenol, guanidine, thiol, indole, imidazole, hydroxyl,sulfate, norbornene, maleimide, laminin, fibronectin, fibrinogen,peptide sequences, or combinations thereof. Bioactive ligands can becovalently incorporated into PEG hydrogels using a thiol-ene-basedphoto-polymerization strategy.

Other PEG formulations may be useful for methods of using the tissueconstructs in, for example, screening applications (i.e., for an agenthaving a certain activity or effect on a cell type within theconstruct). In some cases, PEG formulations comprising non-degradablecrosslinkers are used to obtain neural construct described herein. Inother cases, a hydrogel formed using PEG monomers and comprising variousconcentrations of extracellular matrix-derived peptides or otherpeptides (e.g., peptides comprising the integrin-binding sequence CRGDS(SEQ ID NO:2)) can be used. For example, dextran hydrogels suitable fortissue engineering have been produced by introducing primary aminegroups for covalent immobilization of extracellular-matrix-derivedpeptides (Levesque and Shoichet, Biomaterials27(30):5277-85 (2006)). Inyet other cases, hydrogels comprise different crosslinking densities(i.e., altering stiffness of the hydrogel) or, in some cases, aMMP-degradable crosslinker.

A 3D neural tissue construct of the present invention can be prepared bydispersing isolated cells or an isolated cell population within or on ahydrogel. As used herein, an “isolated cell” is a cell that has beensubstantially separated or purified away from other cell types orbiological substances. As used herein, the term “population” refers to acollection of cells, such as a collection of progenitor and/ordifferentiated cells. As used herein, the term “differentiated” as itrelates to the cells of the present invention can refer to cells thathave developed to a point where they are programmed to develop into aspecific type of cell and/or lineage of cells. Similarly,“non-differentiated” or “undifferentiated” as it relates to the cells ofthe present invention can refer to progenitor cells, i.e., cells havingthe capacity to develop into various types of cells within a specifiedlineage. In exemplary embodiments, a 3D neural tissue construct of theinvention is produced by dispersing one or more defined progenitor cellpopulations (e.g., one or more isolated populations of neural progenitorcells). Preferably, as an initial step, a hydrogel is seeded bydispersing neural progenitor cells within or on a hydrogel. In somecases, the neural progenitor cells are derived from human pluripotentstem cells including, for example, human induced pluripotent stem cells.A hydrogel comprising dispersed neural progenitor cells is then culturedunder conditions and for a length of time sufficient to promotedifferentiation of human neural progenitor cells dispersed therein. Thehydrogel so cultured can be further seeded by dispersing within or onthe cultured hydrogel one or more additional human cell types.Preferably, the hydrogel following dispersal of one or more additionalhuman cell types comprises cell populations such as, for example,pericytes, microvascular endothelial cells, glial cells (e.g.,astrocytes and oligodendrocytes), neuronal cells (e.g., GABAergic andglutamatergic neurons), stromal cells, Schwann cells, undifferentiatedcells (e.g., embryonic cells, stem cells, and progenitor cells),endoderm-derived cells, mesoderm-derived cells, ectoderm-derived cells,and cancer-derived cells or combinations thereof including, withoutlimitation, human endothelial cells, human mesenchymal cells, humanprimitive macrophages, and human pericytes. The hydrogel comprising suchdispersed human cells can be cultured under culture conditions thatpromote cell differentiation for a length of time sufficient to be ableto observe formation of a 3D vascularized neural tissue constructcomprising human neurons and glial cells. Upon differentiation of neuralprogenitor cells and the addition of cell types such as endothelialcells, human mesenchymal cells, human primitive macrophages, and humanpericytes, the resulting three-dimensional neural tissue constructrepresents one or more stages of human brain development.

In some cases, a hydrogel is further seeded by dispersing within or onthe hydrogel one or more bioactive agent that modulates a function orcharacteristic of a cell. Such a bioactive agent can be dispersed withinor on the hydrogel prior to or following dispersal of a cell typedescribed herein.

Advantageously, 3D neural tissue constructs of the invention providephysiologically relevant in vitro models of the developing human brainincluding vascular networks having characteristics of the blood brainbarrier and microglia derived from differentiation of primitivemacrophages. In exemplary embodiments, a 3D tissue construct of theinvention comprises elements important for or involved in development ofthe mammalian (e.g., human, non-human primate) brain including, withoutlimitation, neural progenitor cells, endothelial cells (e.g., humanmicrovascular endothelial cells), mesenchymal cells, and primitivemacrophages. Neural progenitor cells that differentiate within theconstruct provide neuronal and glial populations. Endothelial cells andmesenchymal cells contribute to an interconnected vasculature, andprimitive macrophages differentiate to populate the construct withmicroglia. In some cases, cells populating a tissue construct of theinvention are derived from human pluripotent stem cells, such as humanembryonic stem cells (hESCs) or human induced pluripotent stem cells(iPSCs), under chemically defined, xenogeneic material-free conditions.In exemplary embodiments, human pluripotent stem cells aredifferentiated in vitro under chemically defined, xenogeneicmaterial-free conditions to separately derive distinct tissue constructcomponents as described in Attorney Docket Nos. 960296.01747.P140372US01and 960296.01748.P140410US01, filed concurrently as U.S. applicationSer. No. ______, and U.S. application Ser. No. ______, respectively(serial numbers to be provided). Such cells can self-assemble into aneural tissue construct that lacks vasculature or microglia, or that issubsequently seeded with vascular cells or microglia. In other cases, itis possible to enhance differentiation within a 3D neural tissueconstruct by adding cells that are at intermediate stages such asearlier neural progenitor cells.

In exemplary embodiments, 3D neural tissue construct is produced byculturing neural progenitor cells (e.g., human pluripotent stemcell-derived neural progenitor cells) on a bioactive synthetic hydrogel(e.g., PEG hydrogel) to promote differentiation and self-assembly ofneuronal and glial populations. Such neural progenitor cells can beseeded on a hydrogel at a density between about 10,000 cells/well toabout 500,000 cells/well (e.g., about 10,000 cells/well; 20,000cells/well; 30,000 cells/well; 40,000 cells/well; 50,000 cells/well;75,000 cells/well; 100,000 cells/well; 150,000 cells/well; 200,000cells/well; 250,000 cells/well; 300,000 cells/well; 400,000 cells/well;450,000 cells/well; 500,000 cells/well). Preferably, neural progenitorcells are seeded at a density between about 50,000 to about 200,000cells/well.

Subsequently, vascular cells and microglia precursors (primitivemacrophages) are added to the hydrogel construct. The addition ofvascular cells and primitive macrophages mimics recruitment of bloodvessels and microglia after formation of the neural tube. When culturedon bioactive synthetic hydrogels, the precursors will self-assemble toform complex multilayered, highly uniform neuronal tissue-likeconstructs having similar gross morphological features between samples.Vascular cells and/or primitive macrophages can be seeded on a hydrogelat a density between about 10,000 cells/well to about 500,000 cells/well(e.g., about 10,000 cells/well; 20,000 cells/well; 30,000 cells/well;40,000 cells/well; 50,000 cells/well; 75,000 cells/well; 100,000cells/well; 150,000 cells/well; 200,000 cells/well; 250,000 cells/well;300,000 cells/well; 400,000 cells/well; 450,000 cells/well; 500,000cells/well). Preferably, vascular cells and/or primitive macrophages areseeded at a density between about 50,000 to about 200,000 cells/well.

In exemplary embodiments, a 3D tissue construct is seeded withprogenitors of the myeloid lineages (i.e., granulocyte, macrophage,erythroid, and megakaryocyte) from pluripotent stem cell-derivedhematovascular mesoderm. In humans, common myeloid progenitors (CMPs),which are progenitor cells committed to the myeloid lineages, expressCD34 and IL-3 R alpha (CD123). Progenitors of the myeloid lineages(i.e., granulocyte, macrophage, erythroid, and megakaryocyte) can beseeded on a hydrogel at a density between about 10,000 cells/well toabout 500,000 cells/well (e.g., about 10,000 cells/well; 20,000cells/well; 30,000 cells/well; 40,000 cells/well; 50,000 cells/well;75,000 cells/well; 100,000 cells/well; 150,000 cells/well; 200,000cells/well; 250,000 cells/well; 300,000 cells/well; 400,000 cells/well;450,000 cells/well; 500,000 cells/well). Preferably, progenitors of themyeloid lineages (i.e., granulocyte, macrophage, erythroid, andmegakaryocyte) are seeded at a density between about 50,000 to about200,000 cells/well.

Human hematovascular mesodermal cells can be obtained according to amethod that comprises culturing human pluripotent stem cells for abouttwo days in the presence of a serum-free, albumin-free,chemically-defined culture medium as provided herein that issupplemented to further comprise one or more of the following: a Rhokinase inhibitor (ROCK inhibitor) (e.g., Y-27632), bone morphogeneticprotein 4 (BMP4), Activin A, and lithium chloride (LiCl). In some cases,the human pluripotent stem cells are cultured under hypoxic (i.e.,oxygen level lower than atmospheric) conditions. In exemplaryembodiments, the cells are cultured as described herein in the presenceof 5% O₂. Methods can further comprise obtaining myeloid progenitors byexpanding such pluripotent stem cell-derived hematovascular mesodermalcells under normoxic (i.e., atmospheric oxygen levels, about 20% O₂)conditions in a chemically defined, xeno-free culture medium comprisingor consisting essentially of FGF2, VEGF, TPO, SCF, IL-6, and IL-3. Themethod can comprise the further step of culturing such cells undernormoxic conditions in a myeloid differentiation culture medium. Inexemplary embodiments, a myeloid differentiation culture medium is achemically defined, xeno-free medium comprising granulocyte macrophagecolony-stimulating factor (GM-CSF), which is also known as colonystimulating factor 2 (CSF2) and is a cytokine produced mainly bymacrophages and activated T cells. Recombinant human GM-CSF and relatedproducts are commercially available.

Neural tissue constructs described herein can be modified to havedifferent configurations or morphologies by seeding a construct with alarger or smaller population of neural progenitor cells and,consequently, altering the number, size, and composition (e.g.,identity) of neuron and/or glial cell populations. Likewise, anycellular components or materials used to obtain a neural tissueconstruct as described herein can be modified or optimized to, forexample, tailor a screening method or other use of a neural tissueconstruct provided herein, to assay developmental aspects of humanneural tissue (e.g., modify culture/growth periods, incorporateadditional cell types, remove certain neural tissue constructcomponents), or to vary material properties of a neural tissue construct(e.g., vary adhesion ligand, crosslinking agent, etc.).

Although human cells are preferred for use in the invention, the cellsto be used in tissue constructs of the invention are not limited tocells from human sources. Cells from other mammalian species including,but not limited to, equine, canine, porcine, bovine, feline, caprine,murine, and ovine sources can be used. Cell donors may vary indevelopment and age. Cells can be derived from donor tissues of embryos,neonates, or older individuals including adults.

In some cases, a tissue construct of the present invention may compriserecombinant or genetically-modified cells in place of or in addition tounmodified or wild-type (“normal”) cells. For example, it can beadvantageous in some cases to include recombinant andgenetically-modified cells that produce recombinant cell products,growth factors, hormones, peptides or proteins for a continuous amountof time or as needed when biologically, chemically, or thermallysignaled due to the conditions present in culture. Procedures forobtaining recombinant or genetically modified cells are generally knownin the art, and are described in Sambrook et al, Molecular Cloning, ALaboratory Manual, Cold Spring Harbor Press, Cold Spring Harbor, N.Y.(1989), incorporated herein by reference.

In another aspect, the present invention provides 3D tissue constructscomprising one or more cell types derived from a particular mammaliansubject (e.g., a particular human subject). In some cases, one or morecell types derived exhibit one or more specific phenotypes associatedwith or resulting from a particular disease or disorder of theparticular mammalian subject. Subject-specific cells can be obtained orisolated from a target tissue of interest by biopsy or other tissuesampling methods. In some cases, subject-specific cells are manipulatedin vitro prior to use in a tissue construct of the invention. Forexample, subject-specific cells can be expanded, differentiated,genetically modified, contacted to polypeptides, nucleic acids, or otherfactors, cryo-preserved, or otherwise modified prior to use in a tissueconstruct of the present invention. In some cases, subject-specificcells are differentiated prior to, during, or after encapsulation in athree-dimensional tissue construct of the invention. In other cases,subject-specific cells for use in a tissue construct of the inventionare induced pluripotent stem cells obtained by reprogramming somaticcells of the subject according to methods known in the art. See, forexample, Yu et al., Science 324(5928):797-801 (2009); Chen et al., NatMethods 8(5):424-9 (2011); Ebert et al., Nature 457(7227):277-80 (2009);Howden et al., Proc Natl Acad Sci USA 108(16):6537-42 (2011). Humaninduced pluripotent stem cells allow modeling of drug responses in agenetically diverse population of individuals, including thoseindividuals with genetic diseases. Even the safest drugs may causeadverse reactions in certain individuals with a specific geneticbackground or environmental history. Accordingly, 3D tissue constructscomprising cells derived from iPS cells obtained from individuals havingknown susceptibilities or resistances to various drugs or diseases willbe useful in identifying genetic factors and epigenetic influences thatcontribute to variable drug responses.

In exemplary embodiments, human pluripotent stem cells (e.g., human ESCsor iPS cells) are cultured in the absence of a feeder layer (e.g., afibroblast layer) and in the presence of a chemically defined,xenogen-free substrate. For example, human pluripotent cells can becultured in the presence of a substrate comprising vitronectin, avitronectin fragment or variant, a vitronectin peptide, a self-coatingsubstrate such as Synthemax® (Corning), or combinations thereof. Inexemplary embodiments, the chemically-defined, xeno-free substrate is aplate coated in vitronectin peptides or polypeptides (e.g., recombinanthuman vitronectin).

In another aspect, the present invention provides an organoid culturesystem. As used herein, the term “organoid” refers to a tissue-likestructure (i.e., exhibiting structural properties of a particular tissuetype) that resembles a whole organ and is assembled in vitro by theseparate addition and self-organization of various cell types including,but not limited to, pluripotent stem cells, fetal neural stem cells, andisolated organ progenitors. See, e.g., Lancaster and Knoblich, Science345(6194) (2014). In exemplary embodiments of the invention, an organoidculture system comprises a three-dimensional construct comprisinghydrogel-encapsulated cells and provides a physiologically relevantmicroenvironment for analysis or perturbation of cell-cell interactions,cell-matrix interactions, and morphogenesis in three-dimensionalculture. In some cases, an organoid culture system provides amicroenvironment that at least partially recapitulates tubulogenesis(e.g., capillary tubulogenesis) and vasculogenesis including, forexample, the formation of polarized epithelia with lumens surrounded bycapillary-like structures having endothelial features. In exemplaryembodiments, capillary tubulogenesis in a 3D tissue construct of theinvention recapitulates principles of both angiogenesis, postnatalvasculogenesis, and other developmental steps that closely resembleembryonic neovascularization. Montano et al., Tissue Engineering Part A16(1):269-82 (2010); Kusuma et al., Proceedings of the National Academyof Sciences 110:12601-12606 (2013).

In some cases, a 3D tissue construct of the present invention furthercomprises isolated biological components. As used herein, an “isolated”biological component (such as a protein or organelle) has beensubstantially separated or purified away from other biologicalcomponents in the cell of the organism in which the component naturallyoccurs, such as other chromosomal and extra-chromosomal DNA and RNA,proteins, and organelles. As used herein, the term “isolated protein”includes proteins purified by standard purification methods. The termalso embraces proteins prepared by recombinant expression in a hostcell, as well as chemically synthesized proteins, or fragments thereof.

Engineered three-dimensional tissue constructs of the present inventioncan be prepared, grown, and maintained in any suitable tissue culturevessel that permits production, growth, and maintenance of theconstructs. Suitable vessels include Transwell™ permeable supportdevices and T-75 flasks. In some cases, a 3D tissue construct of theinvention is prepared and/or maintained in a multi-well tissue culturevessel. A multi-well vessel is advantageous to facilitate mechanizationand large-scale or high-throughput screening of neural constructaccording to methods of the invention. For example, a 3D tissueconstruct of the present invention can be prepared or provided using amulti-well tissue culture vessel that facilitates high-throughputassessment of, for example, cellular interactions, in vitro development,toxicity, and cell proliferation upon contacting a chemical compound ofinterest to the neural construct. In some cases, a tissue culture vesselmay be coated with polypeptides or peptides that promote cellproliferation and/or differentiation (e.g., vitronectin, fibronectin)and placed in an incubator at 37° C. prior to seeding with cells.

Any appropriate method or methods can be used to confirm uniformity andthe presence or absence of certain components in a 3D tissue constructprovided herein. Suitable methods for detecting the presence or absenceof biological markers are well known in the art and include, withoutlimitation, immunohistochemistry, qRT-PCR, RNA sequencing, and the likefor evaluating gene expression at the RNA level. In some cases, methodssuch as immunohistochemistry are used to detect and identify cell typesor biomolecules within a 3D tissue construct. For example, whole tissueconstructs or portions thereof can be stained for specificdifferentiation markers by immunohistochemistry. In some cases, it willbe advantageous to perform dual-label immunofluorescence to assess therelative expression of individual marker proteins or to detect multipleprogenitor or differentiated cell types within a construct. Appropriateprimary and secondary antibodies are known and available to thosepracticing in the art. In addition, microarray technology or nucleicacid sequencing (e.g., RNA sequencing) can be used to obtain geneexpression profiles for 3D engineered tissue compositions of theinvention. Myeloid markers and macrophage associated markers include,for example, CD14, CD16, CSFR-1, CD11b, CD206 (also known as macrophagemannose receptor or MMR), CD68, and CD163. Quantitative methods forevaluating expression of markers at the protein level in cellpopulations are also known in the art. For example, flow cytometry isused to determine the fraction of cells in a given cell population thatexpress or do not express biological markers of interest. Biologicalmarkers for perivascular cells and microglia include antibodies havingspecificity to CD45, CD68, or HLA-DR complex.

Differentiation potential of progenitor cells encapsulated in a 3Dtissue construct of the invention can be examined for changes inphenotype, organization, and the presence of certain proteins using, forexample, magnetic sorting, flow cytometry, immunofluorescence,bright-field microscopy, and electron microscopy. In some cases, it willbe advantageous to fix or freeze tissue constructs of the invention forhistology or microscopy. For example, 3D tissue constructs of theinvention can be fixed in formalin or paraformaldehyde for plasticembedment and sectioning using routine methods. Scanning electronmicroscopy (SEM) is useful to detect and analyze the formation oftubular structures in tissue constructs of the invention. In particular,SEM can be used to study cross-sectioned tissue constructs to detectblood vessel formation (e.g., large vessels, small capillaries). Inexemplary embodiments, confocal microscopy can reveal the distributionof cell types and vascular structures throughout a three-dimensionaltissue construct of the invention. In some cases, a three-dimensionalassembly of images obtained by confocal microscopy is used to analyzethe distribution and organization of various cells and structures.

Morphology also can be used to characterize culture components, butcells of different origins may share similar features and be difficultto distinguish using morphology alone. Where appropriate, excitatory andinhibitory synaptic potentials can be analyzed using, for example,extra- or intracellular recording techniques.

TABLE 1 Biological Markers of Differentiated Cell Types in VascularizedNeural Tissue Constructs Cell Type Marker Target Cell Epithelial Tightjunction protein (TJP1); Epithelial tight also known as Zona occludensjunctions protein 1 (ZO-1) Keratin Epithelial (general) Collagen IVEpithelial basement membrane Mesenchymal α-SMA (alpha smooth Pericytesmuscle actin) Vimentin Pericytes PDGFR-β (platelet derived Pericytesgrowth factor receptor beta) Endothelial PECAM-1 (Platelet-Endothelialendothelial cells; Cell Adhesion Molecule-1; also blood vessels known asCD-31) Neuronal N-CAM (neural cell Neurons (including adhesion molecule)postmigratory immature neurons) A2B5 Glial progenitors; oligodendrocyteand astrocyte progenitors

Methods of the Invention

In another aspect, the present invention provides methods for producingand using heterogeneous engineered tissue constructs that mimicstructural elements important for or involved in development of themammalian brain. In particular, provided herein are methods of using 3Dtissue constructs for high throughput screening of candidate compoundsand identifying agents that are toxic to or hinder the development ofone or more components of the tissue construct. The present inventionalso provides methods for screening 3D tissue constructs candidatetherapeutic drugs, modeling a disease or pathological disorder, assaying3D tissue constructs for viability and proliferative capacity of cellsof the construct under various culture conditions, and methods usingneural organoid tissues for compounds exhibiting developmentalneurotoxicity. As described herein, the methods of the present inventionare advantageous over standard in vitro and in vivo methodologies fortoxigenicity testing (e.g., in vivo mouse bioassays for toxigenicitytesting). In particular, the methods described herein provide sensitive,reproducible, and quantifiable methods for neurotoxin screening. Themethods are better alternatives to in vivo mouse bioassays (MBA), anassay which is quantifiable assay but error-prone. In addition, MBArequires a large number of animals and is not easily standardizedbetween laboratories or scalable for high-throughput screening.Shortcomings of the MBA and other animal-based assays have incited apush from regulatory agencies, including the Food and DrugAdministration (FDA) and the United States Department of Agriculture, todevelop cell-based models comprising more physiologically relevant humancells and having the sensitivity and uniformity necessary forlarge-scale, quantitative in vitro modeling and screening applications(National Institutes of Health, 2008).

In exemplary embodiments of methods of the present invention, a 3Dneural tissue construct provided herein is used to screen test compoundsfor known and unknown toxicities. For example, a 3D neural tissueconstruct can be contacted to a test compound and assayed for any effecton any of the cell types contained therein (e.g., neuron, glial cell,vascular cell, microglia, other differentiated cell subtypes). Inexemplary embodiments, screening methods comprise contacting one or moretest compounds to a 3D tissue construct of the present invention anddetecting a positive or negative change in a biological property oractivity such as, without limitation, gene expression, proteinexpression, cell viability, and cell proliferation. The manner in whicha test compound has an effect on a particular biological activity of theconstructs of the present invention will depend on the nature of thetest compound, the composition of the tissue construct and theparticular biological activity being assayed. However, methods of thepresent invention will generally include the steps of (a) culturing a 3Dtissue construct as provided herein with a test compound, (b) assaying aselected biological activity of the artificial tissue construct, and (c)comparing values determined in the assay to the values of the same assayperformed using a 3D tissue construct having the same composition as theconstruct contacted by the test compound but cultured in the absence ofthe test compound (or in the presence of a control). Detecting apositive or negative change in a biological property or activity of acell of the tissue construct can comprise detecting at least one effectof a test compound on morphology or life span of a cell or tissue withinthe contacted tissue construct, whereby a test compound that reduces thelife span of the cells or tissues or has a negative impact on themorphology of the cells or tissues is identified as toxic to humanneural tissue. In some cases, detecting comprises performing a methodsuch as RNA sequencing, gene expression profiling, transcriptomeanalysis, metabolome analysis, detecting reporter or sensor, proteinexpression profiling, Førster resonance energy transfer (FRET),metabolic profiling, and microdialysis. Test compounds can be screenedfor effects on gene expression in the contacted tissue construct, wheredifferential gene expression as compared to an uncontacted tissueconstruct is detected.

In exemplary embodiments, detecting and/or measuring a positive ornegative change in a level of expression of at least one gene followingexposure (e.g., contacting) of a 3D neural construct to a test compoundcomprises whole transcriptome analysis using, for example, RNAsequencing. In such cases, gene expression is calculated using, forexample, data processing software programs such as Light Cycle, RSEM(RNA-seq by Expectation-Maximization), Excel, and Prism. See Stewart etal., PLoS Comput. Biol. 9:e1002936 (2013). Where appropriate,statistical comparisons can be made using ANOVA analyses, analysis ofvariance with Bonferroni correction, or two-tailed Student's t-test,where values are determined to be significant at P<0.05. Any appropriatemethod can be used to isolate RNA or protein from neural constructs. Forexample, total RNA can be isolated and reverse transcribed to obtaincDNA for sequencing.

Test compounds that are suitable for screening according to the methodsprovided herein include any for which one wishes to determine the effectthe compound has on development of the brain of a mammal. It will bereadily apparent to the skilled artisan that the test compounds willinclude those compounds which are suspected of having one or moredeleterious effects on cell or tissue of a 3D construct of theinvention. Ideally, test compounds cover a range of potential celltoxicities including, without limitation, heavy metals (e.g., lead,cadmium) and kinase inhibitors (e.g., MEK inhibitor). Test compounds caninclude FDA-approved and non-FDA-approved drugs (including those thatfailed in late stage animal testing or in human clinical trials) havingknown or unknown toxicity profiles. Test compounds can include thoseincluded in the NIH clinical collection. Some of the toxins, such as MEKinhibitors may affect all or most cell types of a 3D tissue construct.

Any of the cell types can be targeted, including vasculature, microglia,neurons, glial cells, and any interactions between them. Blood brainbarrier junction properties are another example, although we did notstrictly prove we have “blood brain barrier” function (many of theappropriate attachments and genes were expressed, though).

Test compounds can be dissolved in a solvent such as, for example,dimethyl sulfoxide (DMSO) prior to contacting to an engineered tissueconstruct provided herein. In some cases, identifying agents comprisesanalyzing the contacted 3D tissue construct for positive or negativechanges in biological activities including, without limitation, geneexpression, protein expression, cell viability, and cell proliferation.For example, microarray methods can be used to analyze gene expressionprofiles of a 3D tissue construct prior to, during, or followingcontacting the plurality of test compounds to the construct. Geneexpression profiles can be obtained for multiple time points and/ormultiple 3D tissue constructs. In some cases, gene expression profilesdo not directly reflect temporal changes during the initial formation ofvascular networks in sECM but, instead, identify genes robustlyexpressed at each time point. In some cases, a method of the presentinvention further comprises additional analyses such as metabolic assaysand protein expression profiling.

In yet another aspect, the present invention provides methods forevaluating known and potential environmental teratogens. As used herein,the term “teratogen” refers to any environmental factor that can producea permanent abnormality in structure or function, restriction of growth,or death of an embryo or fetus. A method of the invention can comprisecontacting candidate teratogens to a 3D neural tissue constructdescribed herein and screening for developmental abnormalities in theconstruct. Development abnormalities can include, without limitation,vascular malformations, other defects of vascular origin, neoplasias.

In another aspect, the present invention provides methods for in vitromodeling of vascular dysmorphogenesis. In particular, the presentinvention provides a method in which candidate agents are screened forantiangiogenic, neurotoxic, and/or teratogenic effects using a 3D neuralconstruct as provided herein. More particularly, the methods comprisescreening for neurotoxic effects (e.g., inhibition of neuronal growth)and/or detrimental effects on endothelial cells or blood vesselformation (e.g., vascular dysmorphogenesis, angiogenic outgrowth, orblood vessel remodeling) upon exposure to known and unknown agents.Changes in cell viability and proliferative capacity can be detectedusing, for example, cell stains and ³H-thymidine incorporation.

In another aspect, the present invention provides methods for in vitromodeling of neurodegeneration using organoid constructs. In particular,the invention provides an organoid for studying biological phenomenaassociated with neurodegeneration and for detecting or measuring theexpression of genes and proteins associated with neurodegenerativedisorders such as Parkinson's disease. In addition, the organoidconstruct model is useful for screening novel drugs and growth factorsand may reduce the need for invasive animal experiments. A method cancomprise contacting a neural construct described herein to one or morecandidate agents and screening for biological processes associated withneurodegenerative phenotypes including, without limitation,demyelination, axonal damage, protein aggregation, and neurite loss.

It may be advantageous in some cases to employ a machine learningapproach for methods that include, for example, associatingcharacteristic profiles with various cell types and/or withdevelopmental neurotoxicity. For example, in some cases, one or moremachine learning algorithms are employed in connection with a method ofthe invention to analyze data detected and obtained by RNA sequencing orgene expression profiling of 3D neural constructs prior to, during, orfollowing exposure of the constructs to known agents havingdevelopmental neurotoxicity. In addition, one or more machine learningalgorithms can be used to identify gene sets that predict the neuraltoxicity of chemicals even in the absence of pre-existing toxicityinformation. Generally, machine learning algorithms are used toconstruct models that accurately assign class labels to examples basedon the input features that describe the example. In some cases, machinelearning algorithms apply a simple linear separator or a (possiblyweighted) vote of individual features, or distance-based methods. SeeFIGS. 5A-5D and related discussion in the Examples section below.

In some cases, a linear support vector machine (SVM) is used toconstruct a predictive model of developmental neurotoxicity. Generally,SVMs belong to the family of generalized linear models and are useful toconstruct a predictive model for a variable of interest (“the class”)using other variables and training data in which the values of variablesincluding the class are known. A linear SVM is essentially an(n−1)-dimensional hyper-plane that separates the instances of twoclasses in the n-dimensional feature space. Linear SVMs exhibit goodclassification performance on gene expression data. With respect to thepresent invention, a SVM can perform the following task specification:

Given: RNA-seq gene expression measurements for roughly 19K genes on oneday or on several different days following exposure to various drugs,together with a neural toxicity label on each drug.

Do: Construct a model that, from the same type of expression data on anew drug, can accurately identify if the drug is neural toxic.

A linear SVM's output is the weight vector w and the other coefficientb. These are loosely analogous to the coefficients in other linearmodels such as logistic regression, although they are used somewhatdifferently to make predictions on new data points. To make aprediction, the SVM outputs the number w′x_(i)−b, and outputs the label0 (non-toxic) if this number is less than 0, and 1 otherwise. While thenumerical output does not have a probabilistic interpretation as doesthe output of logistic regression, a logistic regression model can bebuilt with one input variable—the SVM's output—from the same trainingset to output a probability of “toxic.”

In exemplary embodiments, the ability of a SVM to predict thedevelopmental neural toxicities of other compounds is estimated. In somecases, an unbiased method that provides relatively high variance isused. In other cases, a nearly unbiased (i.e., slightly pessimistic)method that provides lower variance is used. These methods are standardsin supervised machine learning and statistical classification. Anunbiased method comprises collecting a set of new compounds (notincluded in the training set) but whose neural toxicities are known;generating RNA-Seq data for these compounds; and testing the predictivemodel on them after the model has been constructed. This is consideredto be blinded trial because researchers running the SVM do not knowwhich compounds are included or what fraction of the compounds aretoxic. This information is revealed only after the SVM's predictions aremade.

In some cases, a lower-variance evaluation method, such as leave-one-outcross-validation, is employed. Where there are N data points (compounds)in a training set, the method proceeds in N steps. In each step, adifferent data point is held out of the training set and the SVM istrained on the remaining data points. A prediction is made on theheld-aside data point. Hence every data point is a test case exactlyonce, for a model trained without that data point. Results areaggregated over all the folds, or test cases, to estimate how well theSVM model trained on all the data will perform on a new data point(compound). The method has lower variance because it tests on morecompounds—all the compounds of the training set—but is slightlypessimistic because each training set is slightly smaller (one less)than the actual training set.

Using the above leave-one-out cross-validation methodology, numbers oftrue positive (toxic) predictions (TP), as well as false positive (FP),true negative (non-toxic, TN), and false negative predictions (FN) arecomputed. Using these numbers, accuracy (i.e., fraction of predictionsthat are correct) can be computed. In addition, one can computesensitivity, or true positive rate, or recall [TP/(TP+FN)]; specificity[TN/(TN+FP)]; and precision, or positive predictive value [TP/(TP+FP)];and other metrics such as F-measure and negative predictive value.Nevertheless, all of these metrics depend on not only the model thatproduces probabilistic predictions for toxicity but also the probabilitythreshold at which we make positive predictions, such as 0.5. Hence itis common in machine learning and statistical classification to report“thresholdless” curves and or metrics, the most popular being thereceiver operating characteristic (ROC) curve and the area under thiscurve (AUC). The ROC curve plots true positive rate on the y-axisagainst the false positive rate (1-specificity) on the x-axis as thethreshold is varied. Random uniform guessing produces a diagonal fromlower left to upper right corner and AUC of 0.5, while perfectprediction produces a graph that goes up to the upper left corner andthen across and AUC of 1.0.

In a further aspect, provided herein is a tissue construct screeningsystem. A tissue construct screening system can comprise an analyticaldevice configured to obtain data comprising measurements from a 3D humanvascularized neural tissue construct provided herein. The system canfurther comprise a computer controller configured to receive the datafrom the analytical device; and a machine-based adaptive learning systemtrained using known gene expression data and configured to select asubset of features from the data using a feature selection algorithm.The subset of features corresponds to a change in a level of expressionof at least one gene following exposure to a known or unknown testcompound. In some cases, the measurements comprise gene expression dataobtained from microarrays.

Unless defined otherwise, all technical and scientific terms used hereinhave the same meaning as commonly understood by one of ordinary skill inthe art to which the invention belongs. Although any methods andmaterials similar to or equivalent to those described herein can be usedin the practice or testing of the present invention, the preferredmethods and materials are described herein.

As used herein, “a medium consisting essentially of” means a medium thatcontains the specified ingredients and those that do not materiallyaffect its basic characteristics.

As used herein, “serum-free” means that a medium does not contain serumor serum replacement, or that it contains essentially no serum or serumreplacement. For example, an essentially serum-free medium can containless than about 1%, 0.9%, 0.8%, 0.7%, 0.6%, 0.5%, 0.4%, 0.3%, 0.2% or0.1% serum.

As used herein, “effective amount” means an amount of an agentsufficient to evoke a specified cellular effect according to the presentinvention.

As used herein, “about” means within 5% of a stated concentration range,density, temperature, or time frame.

The invention will be more fully understood upon consideration of thefollowing non-limiting Examples. It is specifically contemplated thatthe methods disclosed are suited for pluripotent stem cells generally.All papers and patents disclosed herein are hereby incorporated byreference as if set forth in their entirety.

EXAMPLES Example 1 Producing Vascularized Neuronal Tissue Constructs

Hydrogel Polymerization:

Thiol-ene photo-polymerization provides mix and match adaptability forcustomizing hydrogels, since any peptide that includes cysteine in theamino acid sequence can be coupled into a hydrogel. Polyethylene glycol(PEG) hydrogels were formed using thiol-ene photopolymerizationchemistry, with modifications from previously a published protocol(Fairbanks et al., Adv Mater 21(48):5005-5010 (2009)). Stock solutionsof 8-arm PEG-norbornene (20000 MW, JenKem USA, 8ARM (TP)-NB-20K) wereprepared at a final concentration of 300 mg/mL by dissolving 300 mg ofsolid/0.8 mL PBS to account for volume occupied by 8-arm PEG-norbornenesolid, sterile filtered through a 0.2 μm nylon syringe filter (Fisher),and stored as frozen aliquots. Matrix metalloproteinase (MMP)-degradablePEG hydrogels were formed using an amino acid sequence modified from anative collagen sequence (Nagase et al., Biopolymers 40(4):399-416(1996)) (KCGPQG˜IWGQCK (SEQ ID NO:1); Active sequence in bold, cleavesite=(˜); Genscript, >90% purity, C-terminus amidated), with cysteineson each end to crosslink 8-arm PEG-norbornene molecules. Cell adhesionwas promoted by incorporating CRGDS peptide (SEQ ID NO:2) (2 mM finalmonomer solution concentration; Genscript, >90% purity, C-terminusamidated), an amino acid sequence derived from fibronectin(Pierschbacher et al., Nature 309(5963):30-33 (1984)). Stock MMP-peptide(˜75 mM peptide/150 mM SH) and CRGDS peptide (˜100 mM) solutions wereprepared and sterile filtered through a 0.22 μm low protein bindingpolyvinylidene difluoride (PVDF) syringe filter (Millex) and the finalconcentration was verified after filtration using an Elman's assay(Thermo Scientific; modification of Manufacturer's protocol: PBS used todissolve all reagents).

As shown in FIGS. 2A-2D, biophysical and biochemical properties ofthiol-ene hydrogels are tunable and influence cell properties. Forexample, spreading of mesenchymal stem cells (MSCs) is a function ofdegradation rate and adhesion ligand density. MSC attachment andspreading was tuned by varying adhesion ligand density (using thefibronectin mimic CRGDS) or the susceptibility of the crosslinker toproteolytic degradation (by varying the P′₂ position of the amino acidsequence). MSC spreading was maximized with Tryptophan (W) in the P′2position of the amino acid sequence and 1000 mM RGD (FIG. 2A), whileMSCs remained rounded in hydrogels having the most degradablecrosslinker (Tryptophan in the P′2 position) but lacking an activeadhesion peptide (FIG. 2B). Only limited spreading was observed whenTryptophan was replaced with Ala due to lower susceptibility to MMPdegradation (FIG. 2C), while intermediate spreading was observed whenTryptophan was replaced with Leucine (FIG. 2D). Human umbilical veinendothelial cells (HUVECs) are viable when grown in 3D syntheticextracellular matrices, but the presence of different RGD concentrationsaffected 3D organization (FIGS. 2C-2D). Human dermal fibroblasts grownin 3D synthetic matrix (relative to growth on collagen) demonstrate thatthe basic morphology and cytoskeletal structure of the resulting tissueconstructs is indistinguishable from natural extracellular matrices. Itwas also observed that cell attachment and spreading of human MSCs inthree dimensions are affected by choice of adhesion ligand density andproteolytically degradable crosslinker.

For subsequent assays, the final monomer formulation for PEG hydrogelswas 40 mg/mL 8-arm PEG-NB, 4.8 mM MMP-peptide crosslinker (9.6 mMcysteines, 60% molar ratio relative to norbornene arms), 2 mM CRGDS (SEQID NO:2), and 0.05% (wt/wt) Irgacure® 2959 photoinitiator (BASF SchweizAG, Basel, Switzerland). Hydrogels were formed by pipetting 30 μLmonomer into 24-well BD Transwell inserts (1 μm pores, Fisher; Qualitycontrol experiments) or 40 μL into Corning HTS Transwell-24 wellpermeable support (0.4 μm pores, Sigma Aldrich; Toxicity experiments).After pipetting, any gaps between the PEG monomer solution and the edgeof the insert (due to surface tension) were removed by tilting theinsert plate and gently tapping until the solution uniformly covered thebottom of the transwell insert membrane. Transwell plates containinginserts and monomer solutions were placed on the top shelf of a UVPXX-15 lamp stand (Fisher) and exposed to ˜365 nm centered UV light (UVPXX-15L lamp, Fisher) for 2.5 minutes. After polymerization, hydrogelswere incubated in DF3S medium overnight to allow swelling andequilibration (5% CO₂, 37° C.).

Seeding Porous Biomaterials with Pluripotent Stem Cell-Derived NeuralProgenitor Cells:

Vascularized neural tissue constructs were obtained according to thestrategy generally depicted in FIG. 1B. Neural and astrocyte precursorswere overlayed onto the cell-embedded PEG hydrogel and cultured forabout two weeks. Specifically, cryopreserved neural progenitor cells(NPCs) were thawed and expanded on 6-well plates coated with Matrigel®(BD Biosciences, 0.5 mg per plate for at least 1 hour) and cultured inneural expansion medium. One vial of frozen NPCs (1.2×10⁷ cells) werethawed and plated in 3 wells of a Matrigel® coated 6-well plate (2 vialswere thawed in one Matrigel® coated 10 cm dish), cultured for 2-3 days(depending on initial confluence) and passaged 1:3 using Accutase™ NPCswere passaged 1:3 after 2 days of additional culture, expanded for 2-3more days and used for experiments. NPCs were removed from the plateusing 1 mL Accutase/well, from which an aliquot was removed forcounting. After adding the appropriate volume of cell suspension to aconical vial, NPCs were pelleted at 0.2 G for 4 minutes. NPCs wereresuspended and seeded in neural expansion medium at a density of100,000 cells/24-well insert. NPCs were allowed to attach overnight, andthen neural expansion medium was exchanged on Day 1 and every 2 days forthe remainder of the experiment. For each medium exchange, all mediumunder the insert was aspirated, while approximately 3/4 of the mediumwas removed from the top by sliding the pipette tip down the side of thewell to avoid damaging the developing neural tissue constructs.

As described in the following sections, the resulting vascularizedneural tissue construct mimics in vivo cephalic mesenchyme-neuralepithelial interactions. neural progenitor cells and/or componentsderived from such progenitors are introduced by adding the components tothe top of a three-dimensional tissue construct.

Differentiation and Growth of Pluripotent Stem Cell-Derived EndothelialCells (ECs) and Mesenchymal Stem Cells (MSCs):

Endothelial cells were expanded from cryopreserved stocks onfibronectin-coated plates (Life Technologies, 100 μg per plate) usingE7BV media, with one vial (˜1×10⁶ cells) per 6 wells of a 6-well plateor a single 10 cm dish. ECs were split 1:3 after 2 days using Accutase,cultured for an additional 3 days, and then used for experiments. E8BAmedium: E8 supplemented with BMP4 (5 μg/L) and Activin A (25 μg/L). E7Vmedium: E8 minus TGFβ1, supplemented with VEGF-A (50 μg/L). E7BVimedium: E7V supplemented with BMP4 (50 μg/L) and SB431542 (5 μM, TGFβinhibitor) (Inman et al., Mol Pharmacol 62(1):65-74 (2002)).

At day 9, ECs and MSCs were seeded on top of the differentiating NPClayer at a total density of 100,000 cells/well, with a 5:1 ratio ofECs:MSCs (83.3K:16.7K). Both ECs and MSCs were harvested using Accutaseand counted before centrifugation. Cells were counted and mixed in theappropriate ratio, centrifuged, and resuspended for seeding. Neuralexpansion medium was exchanged on day 11 (2 days after seeding ECs andMSCs). At day 13, microglia/macrophage precursors were harvested andseeded at a density of 100,000 cells/insert. Neural expansion medium wasexchanged on day 14, and then every other day until samples werecollected for RNA, sorting, or immunofluorescence imaging.

Addition of Primitive Macrophages to Neural Constructs:

Primitive macrophages were added to hydrogel neural tissue constructsafter initial vascular network organization and after neural progenitorcells had self-assembled into multilayered structures with radiallyorganized neural and glial populations (see FIG. 8) reminiscent of theearly neuroepithelium.

The neuronal tissue constructs were characterized by several featuresthat resembled the human neocortex during early development of thecortical plate.

Immunofluorescence imaging and RNA-sequencing provided evidence fordiverse neuronal and glial phenotypes, including interneurons andprojection neurons (FIGS. 3A-3I). Radially oriented GFAP⁺ and Vimentin⁺cells were consistent with radial glia, and a densely packed cellularlayer characterized by stratification of cortical neurons resembledfeatures of the mammalian cortex, such as previously reported for humanpluripotent stem cell-derived 3D in vitro neuronal tissues (Lancaster etal., Nature 501:373 (2013); Kadoshima et al., Proc. Natl. Acad. Sci.U.S.A 110:20284 (2013); Mariani et al., Proc. Natl. Acad. Sci. 109:12770(2012); Eiraku et al., Cell Stem Cell 3:519 (2008)). For example, areelin⁺ layer at the outer tissue edge and an adjacent layer abundantwith calretinin⁺ neurons assembled similarly to Cajal-Rezius neurons inthe marginal zone and interneurons of the emerging human cortical plateat ˜7-9 gestational weeks (GW).

In summary, our neuronal constructs were characterized by corticalorganization and stratification that was consistent with 3D neuronaltissues in vitro and features described for the human neocortex duringdevelopment. Importantly, it is our understanding that these neuronaltissue constructs provide the first in vitro model of human corticaldevelopment that was formed using a synthetic hydrogel (rather thanMatrigel or suspension culture) and that, in some embodiments, comprisesmicroglia derived from human pluripotent stem cells. Moreover, theneuronal tissue constructs described herein are believed to be the firstto incorporate vasculature, to be formed using methods that can beeasily automated or scaled for high throughput protocols, and, asdescribed in the following Example, the first in vitro three-dimensionalneural “organoids” useful for quantitative toxicity screening and forsuccessfully predicting neural toxicity (in a blinded study).

The timing for vascularization of the human cerebral cortex parallelsemergence of the cortical plate, when angiogenic sprouts from the pialcapillary plexus begin penetrating the neural tube. Endothelial cellsformed extensive vascular networks by day 16 (FIGS. 4A-4C), whilecapillary-like structure was more organized and extended throughout theneuronal constructs by day 21 (FIGS. 4D-4F). Vascular networkspenetrated into the layered regions and extended around thecircumference of the neuronal constructs (FIGS. 4E-4F), and bothmesenchymal (FIG. 4G) and glial (FIG. 4H) cells wrapped capillary-liketubules and larger vessel-like structures on the periphery. Further,capillary-like tubules aligned with radial glia (FIG. 4I), especially atthe leading edge of the extending vascular network (FIG. 4K). Glialcells attached to capillary-like tubules through end-feet (FIGS. 4J-4K),suggesting that the neuronal constructs mimicked at least some aspectsof the blood-brain-barrier (BBB). By day 21, the constructs contained anextensive neural network, cells exhibiting neural and glial phenotypes,interconnected capillary networks, and microglia-like cells. Notably,vascular network formation was induced within the neuronal constructswithout the requirement for exogenous addition of growth factors such asVEGF. Further, RNA-sequencing demonstrated that genes for several bloodvessel-promoting growth factors were highly expressed within theneuronal constructs for control samples without vascular cells (e.g.,VEGFA and PDGFB). Therefore, cellular signaling within the neuronalconstruct provided the necessary cues to induce vascularization, whichis consistent with initial recruitment of capillaries to the cerebralcortex by the neuroepithelium.

Several microglia genes were expressed only after primitive macrophageswere added to the neuronal constructs (e.g., AIF1/IBA1, TREM2). Further,IBA1⁺ (AIF1) cells with ramified morphologies were distributedthroughout the neuronal constructs by day 21 (FIGS. 5A-5D), which isconsistent with microglia in the resting state. Some IBA1⁺ cells alsointeracted with capillary-like tubules within the neuronal constructs(FIGS. 5B-5C), which has been observed during human development and mayindicate a role for microglia in guiding vascular organization.Therefore, the 3D neuronal constructs provided the necessary cues toinduce primitive macrophages to adopt a phenotype characterized byseveral hallmark features of microglia.

RNA sequencing (RNA-Seq) was used to quantitatively assess sampleuniformity by comparing differential gene expression for replicateneural constructs after 14 and 21 days of differentiation on hydrogels.In addition, replicate samples were characterized by Spearman'scorrelation coefficients (ρ)≧0.99 to at least 21 days ofdifferentiation. RNA-Seq revealed an increase in expression of CD68, amicroglial cell marker. RNA-Seq also identified several characteristicmicroglia genes that were detectable only when primitivemacrophages/microglia precursor cells were incorporated into the neuralconstructs, such as CD11B (ITGAM), TREM2, and IBA1 (AIF1). See FIGS.7A-7C and Tables 2 and 3. RNA-Seq identified differentially expressedgenes for day-21 neural constructs compared to H1 ES cells (in normalculture), and characteristic gene ontology (GO) clusters were identifiedfrom the resulting gene sets using the DAVID functional annotationdatabase (Huang et al., Nat. Protocols 4(1):44-57 (2008); Ashburner etal., Nature Genet. 25:29-29 (2000)). Neural constructs werecharacterized by 4865 upregulated and 4669 downregulated genes relativeto H1 ES cells (FDR≦0.005). Upregulated genes for the neural constructswere enriched within GO categories that included neuron differentiation(GO:0030182, 212 genes), forebrain development (GO:0030900, 52),hindbrain development (GO:0030902, 31), synaptic transmission(GO:0007268, 143), vasculature development (GO:0001944, 85 genes), andothers. A wide variety of expressed genes within the neural constructshave previously been identified for roles in human cortical layering,including marginal zone and layer I neurons (GAP43, Reelin/RELN andCalretinin/CALB2), upper layer neurons (e.g., CUX1, SATB1), and deeplayer neurons (e.g., CTIP2/BCL11B, ETV1, FOXP1, SOX5) (Bayatti et al.,Cereb. Cortex 18(7):1536-1548 (2008); Meyer et al., J. Neurosci.20(5):1858-1868 (2000); Zecevic et al., The Journal of ComparativeNeurology 412(2):241-254 (1999); Saito et al., Cereb. Cortex21(3):588-596 (2011); Ip et al., Cereb. Cortex 21(6):1395-1407 (2011).Therefore, RNA-seq identified diverse cellular phenotypes within theneural constructs and suggested a role for neurodevelopmental mechanismsin the emergence complexity within the tissue.

Iba-I protein expression was detected by fluorescent antibody staining.Iba1⁺ cells were distributed throughout the neural constructs by day 21,and adopted ramified morphologies, which is a distinguishing feature formicroglia in the resting state. Iba1⁺ cells associated with endothelialtubules, which has been observed during human development and suggests apossible role for microglia in guiding vascular organization within theneural constructs. Therefore, human ES cell-derived primitivemacrophages exhibit several properties consistent with a microglia-likephenotype observed within the neural constructs.

Human ES cell-derived neural progenitor cells alone self-assembled intomultilayered tissue-like structures when cultured on degradablebiomaterials such as MMP-degradable PEG hydrogels (FIGS. 6A-6B) whereasself-organization was less pronounced on non-degradable hydrogels,demonstrating that remodeling of the hydrogel components influences theself-assembly and organization of neural progenitor cells intothree-dimensional tissues. It is important to note that both degradableand non-degradable hydrogel construct formats are useful for studyingthe effect of altering material properties of the construct on the cellsand tissues within the construct. In addition, the physical and chemicalproperties of the two formats may be beneficial for particular screeningapplications and other uses as described herein.

In sum, these data demonstrate that three-dimensional multilayeredneural tissue-like constructs can be produced with remarkable uniformitywhen ES cell-derived precursor cells are cultured on bioactivehydrogels.

TABLE 2 Gene Expression in Neural Constructs Average Standard DeviationGenes Day 16 Day 21 Day 16 Day 21 AIF1/IBA1 12.1 15.6 3.3 8.8 ITGAM/CD2.3 1.2 0.6 1.2 PTPRC 4.1 3.6 0.9 3.3 CX3CR1 3.8 3.7 0.8 4.6 CD68 17.323.8 4.0 18.9 CD14 1.8 3.0 1.6 1.4 Normalized expression (TPM; N = 4)

Example 2 Methods and Materials

Human Embryonic Stem (ES) Cell Culture:

Essential 8 (E8) Medium (1):

DMEM/F12 HEPES (Life Technologies, 11330-032), L-ascorbicacid-2-phosphate magnesium (64 mg/L; Sigma-Aldrich, A8960-5G), sodiumselenite (14 μg/L; Sigma-Aldrich, S5261), NaHCO3 (543 mg/L),holo-transferrin (10.7 mg/L; Sigma-Aldrich, T0665-1G), insulin (20 mg/L;Sigma-Aldrich, 19278), human recombinant FGF2 (rhFGF2, 100 μg/L), andTGFβ1 (2 μg/L; R&D Systems, 240-B-001MG/CF).

H1 human embryonic stem (ES) cells were maintained in E8 medium (1)(Life Technologies) on Matrigel (growth factor reduced, Corning 356230)coated culture plates and were passaged with 0.5 mM EDTA in 1×PBS aspreviously described (2). Cells were karyotyped within 10 passages andtested negative for mycoplasma contamination.

Human ES Cell Differentiation into Neural Progenitor Cells (NPCs):

DF3S Medium:

DMEM/F-12, L-ascorbic acid-2-phosphate magnesium (64 mg/L), sodiumselenium (14 μg/L), and NaHCO3 (543 mg/L).

Essential 6 (E6) Medium:

DMEM/F-12, L-ascorbic acid-2-phosphate magnesium (64 mg/L), sodiumselenite (14 μg/L), NaHCO3 (543 mg/L), transferrin (10.7 mg/L), andinsulin (20 mg/L).

Neural Expansion Medium:

DF3S medium supplemented with rhFGF2 (5 μg/L), 1×N2 (Life Technologies,17502-048) and 1×B27 (Life Technologies, 17504-044) supplements.

The procedure for deriving neural progenitor cells was modified from apreviously reported protocol (3). H1 ES cells were split using 0.5 mMEDTA in 1×PBS and cultured in E6 medium supplemented with rhFGF2 (100μg/L) and SB431542 (TGF-β receptor inhibitor, 10 μM; Sigma-Aldrich).After two days, the medium was switched to E6 medium supplemented withSB431542 (10 μM) for seven days with daily media exchange to induce theformation of neural rosettes. The neural rosettes were then mechanicallydissociated from the culture dish and cultured as floating aggregates inneural expansion medium for four days. Aggregates were then dissociatedwith Accutase (Life Technologies) and plated onto Matrigel (growthfactor reduced, Corning 356230) coated plates in neural expansionmedium. Cells were cultured for an additional 22 days and passaged whenconfluent, yielding >90% SOX1+/βIII-tubulin+neural progenitor cells(“NPCs”). NPCs were cryopreserved at 1.2×107 cells per vial.Cryopreserved neural progenitor cells were used for subsequent expansionand formation of 3D neural constructs to ensure a uniform cell sourcefor all experiments.

Human ES Cell Differentiation into Endothelial Cells (ECs):

E8BA Medium:

E8 medium supplemented with BMP4 (5 μg/L) and Activin A (25 μg/L).

E7V Medium:

E8 medium minus TGFβ1, supplemented with VEGF-A (50 μg/L).

E7BVi Medium:

E7V supplemented with BMP4 (50 μg/L) and SB431542 (5 μM, TGFβinhibitor)(4).

H1 ES cells (80-90% confluent) were dissociated using TrypLE(Invitrogen) for three minutes at 37° C. and plated 1:3 onvitronectin-coated plates (60 μg/10 cm dish, VTN-N, LifeTechnologies)(1). ES cells were first cultured for two days (to 100%confluence) in E8BA medium, which was supplemented with 10 μM Y-27632for the first day to improve cell survival during attachment. It iscritical to achieve 100% cell confluence by day 2 to ensure highlyefficient differentiation. Cells were then cultured in E7BVi medium foran additional three days. Endothelial cells were then isolated with CD34microbeads (Miltenyi) by autoMACS (Miltenyi) to yield purifiedpopulations of CD34⁺/CD31⁺ cells (“ECs”). The purified endothelial cellswere either cryopreserved immediately or cultured on fibronectin-coatedplates in E7V medium for one passage before cryopreservation.

Human ES Cell Differentiation into Mesenchymal Stem Cells (MSCs):

Mesenchymal Serum Free Expansion Medium (M-SFEM):

50% StemLine II serum-free HSC expansion medium (HSFEM; Sigma-Aldrich),50% human endothelial serum-free medium (ESFM; Invitrogen), GlutaMAX(1/100 dilution; Invitrogen), Ex-Cyte supplement (1/2000 dilution;Millipore), 100 mM monothioglycerol (MTG), and 10 μg/L rhFGF2.

Mesenchymal stem cells (MSCs) were derived from H1 ES cells using apreviously published protocol (5). Tissue culture polystyrene plateswere coated with human fibronectin (5 mg/mL; Invitrogen) and humancollagen I (10 mg/mL; BD Biosciences) in phosphate buffered saline (PBS)for expansion and Accutase (StemPro) was used for passaging. MSCs wereexpanded for five passages in M-SFEM (5), followed by two passages inpericyte medium (ScienCell), and then cryopreserved (PDGFRB⁺CD13⁺,“MSCs”).

Human ES Cell Differentiation into Microglia/Macrophage Precursors (MG):

Microglia/macrophage precursors were produced using feeder-freeconditions by modifying a previous protocol for differentiating H1 EScells down mesendoderm and hemogenic endothelium lineages (see Uenishiet al. (2014) Stem Cell Rep 3(6):1073-1084). E-well plates were firstcoated with 40 μg Tenascin C overnight at 4° C. Tenascin C plates wererinsed with PBS, and then seeded with singularized H1 ES cells at adensity of 62,500 cells/cm² in E8 medium+10 μM Y-27632 (ROCK inhibitor,R&D Systems). Cells were cultured for 24 hours under normoxicconditions.

Initiate Early Mesoderm Differentiation.

24 hours after plating H1 ES cells, E8 media was aspirated and replacedwith DM1+1 μM Y-27632. Cells were then cultured under hypoxic conditions(5% O₂) for two days (do not expose cells to normoxia). During the twodays of culture, cells detach and reattach. It is important that theculture is not disturbed, as cells will aggregate in the middle of theplate, affecting differentiation efficiency.

Continue Hematovascular Mesoderm Differentiation.

On day two, the culture was checked for surviving cell clumps that hadnot fully reattached. If non-adherent cells were present, a 10 mLpipette tip was used to gently pull media off plate, and thenon-adherent cells and cell clumps were centrifuged at 300×g for fiveminutes to form a pellet. DM1 was aspirated from the pellet, and thecells were resuspended in DM2. Cells were gently plated back into sameplate, and culture was continued in a hypoxic incubator. If only debriswas present, DM1 was aspirated and DM2 was added slowly as to notdisrupt the adherent cells. Culture was continued in a hypoxicincubator.

Differentiate and Expand Hemogenic Endothelial Cells into HematopoieticProgenitor Cells (HPCs).

On day 4, DM2 medium was aspirated and replaced with DM3 medium. Culturewas continued under normoxic conditions. On day 6 of culture (two daysafter adding DM3 media), additional DM3 media was added withoutaspirating media already present. Culture was continued in a normoxicincubator. Cell cultures were expanded for an additional 3-5 days in DM3(longer time is required when cells not fully adherent afterhematovascular differentiation). If media color indicated a significantpH drop, half of the media volume was removed from the plate and placedinto a low attachment dish. An additional volume of DM3 (1:1 mix of oldand fresh media) was added to both culture plates. After 3-5 days, spentmedia containing non-adherent HPCs was collected and centrifuged at300×g for about five minutes to pellet.

Myeloid Progenitor (MP) Differentiation.

Expansion was continued in myeloid progenitor medium DM4, where 1×10⁶HPCs/mL were to a low attachment culture dish under normoxic conditions.At this point, the cells could be grown in a 10 cm dish under normoxicconditions. Cells were expanded for 2-5 days in the DM4 medium. At leastfive days in culture was required for proper transition to macrophages,but no more than five days. DM4 was added if the culture's pHsignificantly dropped (half/half mixture; do not transfer cells). Up to2×10⁷ cells were obtained from a 10 cm dish. During expansion in DM4medium (2-5 days), non-adherent cells were collected for sorting toidentify CD34⁺ and CD45⁺ cells.

Microglia/Macrophage Precursor (MG) Differentiation.

After 2-5 days of myeloid progenitor expansion, 5×10⁵ non-adherent cellswere added to macrophage differentiation medium DM5 in a 10 cm tissueculture treated dish. Cells were cultured for three days, then anequivalent volume of DM5 media was added without aspiration of themedia. After five days (two additional days in DM5), ˜50-70% of cellshad attached. When cells reached ˜70-80% confluence (adherent cells),remaining non-adherent cells were transferred to a new 10 cm dish topromote adhesion. Both adherent and non-adherent populations are CD45⁺,but non-adherent cells will be CD14^(Low/Negative) and adherent cellswill be CD11b⁺/CD14⁺. On days 5-10, non-adherent cells began to attachand differential into CD11b⁺ and CD14⁺ cells. Culture in DM5 medium wascontinued.

For the quality control assays, RNA was collected on days 14 and 21. Forthe 3D toxicity screening experiments, RNA was collected on days 16 and21 (permitting 2 days of chemical exposure before collecting at thefirst time point).

Immunofluorescence Imaging:

Blocking buffer: 0.25% Triton X-100 and 1% BSA in PBS; Incubationbuffer: 0.05% Triton X-100 and 1% BSA in PBS; Rinse buffer: 0.05% TritonX-100 in PBS.

Primary Antibodies:

Rabbit anti-β3-tubulin (1:500; Cell Signaling, mAb #5568S), mouseanti-β3-tubulin (1:500; R&D Systems, MAB1195), rabbit anti-calretinin(1:100-1:200: Abcam, ab137878), rabbit anti-GABA (1:200: Abcam,ab43865), rabbit polyclonal fibrillary acidic protein (GFAP) (1:500;Dako, Z033401-2), goat anti-glialfibrillary acidic protein (GFAP)(1:100-1:200; C-19; sc-6170, Santa Cruz Biotechnology), mouseanti-phospho-vimentin (1:200; S55 [4A4]; Abcam, ab22651), mouseanti-CD31 (1:200; Endothelial Cell, Clone JC70A; DAKO, M082301-2), mouseanti-04 (1:100-1:200; clone 81; Millipore, MAB345), Chicken polyclonalanti-Tbr1 (1:100-1:200; Millipore, AB2261), mouse anti-SOX-2 (CellSignaling, mAb #4900S), rabbit anti-SOX-2 (Cell Signaling, mAb #3579S),mouse anti-MAP2, (clone AP20; Millipore, MAB3418), mouse anti-Reelin(1:100; clone G10, a.a. 164-496; Millipore, MAB5364), mouse anti-Brn-2(POU3F2) (1:200; clone 8C4.2; Millipore, MABD51), rabbit anti-Brn-2(POU3F2) (1:200; Cell Signaling, mAb #12137S), rabbit anti-Ctip2(Bcl-11b) (1:200; Cell Signaling, mAb #12120S), rabbit anti-VGLUT2(1:100; Abcam), mouse anti-MAP2 (1:500; clone AP20; Millipore, MAB3418),goat anti-Iba1 (1:100; Abcam, ab5076), rabbit anti-Tyrosine Hydroxylase(Cell Signaling, mAb ##27925), rabbit anti-PDGFR-α (1:100; Santa CruzBiotechnology, sc-338).

Secondary Antibodies:

Alexa Fluor secondary antibodies were used for all experiments (LifeTechnologies): Donkey anti-goat 568 (A11057) or 647 (A21447); Donkeyanti-rabbit 488 (A21206), 568 (A10042), or 647 (A-31573); Donkeyanti-mouse 488 (A-21202), 568 (A10037), or 647 (A31571); Goatanti-chicken (A11041).

Immunostaining Full Neural Constructs:

All steps for immunostaining were performed within transwell inserts.Neural constructs were fixed for 60 min. using 2% buffered formalin andthen rinsed with PBS (or stored at 4° C. until immunostaining). Neuralconstructs were permeabilized and blocked in blocking buffer (at least60 min.). For some experiments, blocking buffer was used for all stepsuntil final rinse, with similar results. Primary antibodies wereprepared in incubation buffer, added to the neural constructs, andincubated overnight at 4° C. Neural constructs were then rinsed (2× withrinse buffer, at least 60 min./ea.) followed by a third rinse step(blocking buffer, at least 60 min.). Secondary antibodies and 1:1000DAPI (Sigma) were prepared in incubation buffer, added to the neuralconstructs, and incubated overnight at 4° C. (or at least 4 hours atroom temperature). Neural constructs were rinsed 2×60 min. in rinsebuffer, followed by an overnight rinse at 4° C. in incubation buffer.Samples were then stored in PBS until further processing (typically atleast 24 hours).

Neural constructs were removed from the transwell insert by cutting thebottom edge of the membrane, separated from the membrane, and mounted inaqua polymount solution (Polysciences, Inc.) on the bottom of a 35 mmglass bottom dish (MatTek). To limit bubble formation in the mountingsolution, a thin layer was first added to the glass bottom of the 35 mmdish. The neural construct was usually placed face down into the layerof mounting solution (with some samples placed face up), after which adrop of mounting solution was added to cover the construct. A coverslipwas then dropped onto the neural construct in mounting solution andallowed to settle, rotating the dish to ensure uniform coverage of themounting solution under the coverslip. The coverslip was allowed tosettle overnight at 4° C., and sealed around the edges with fingernailsealant. The samples remained stable for imaging for at least 1 month.

Immunostaining Cryopreserved Sections:

Neural constructs were fixed in the transwell insert for 60 min. using2% buffered formalin and rinsed with PBS (overnight at 4° C.). Thesamples were then rinsed in 15% Sucrose/PBS (at least 24 hours, 4° C.)followed by 30% Sucrose/PBS (at least 24 hours, 4° C.). Neuralconstructs were removed from the transwell insert by cutting the bottomedge of the membrane, separated from the membrane, and placed face downinto cryogel (Tissue-Tek embedding medium), and stored frozen at −80° C.until further processing. Frozen samples were equilibrated to −20° C.and sectioned (20-30 μm sections on glass slides). Glass slidescontaining sectioned samples were soaked in deionized water for at least1 hour to remove cryogel. Samples were permeabilized and blocked inblocking buffer for 60 min., rinsed 2×15 min. with rinse buffer, andincubated at room temperature in incubation buffer for at least 60 min.Samples were then treated primary antibodies in incubation buffer at 4°C. (or at least 4 hours at room temperature). Samples were then rinsedwith wash buffer (2×15 min.) and incubation buffer (at least 60 minutes,room temperature). Samples were then treated with secondary antibodiesand 1:1000 DAPI (Sigma) in incubation buffer overnight at 4° C. (or atleast 2 hours at room temperature). Sectioned samples were mounted inaqua polymount solution (Polysciences, Inc.), a glass coverslip wasplaced over the top, stored overnight at 4° C., and sealed around theedges with fingernail sealant until imaging.

Image Processing:

Confocal immunofluorescence images were collected using a Nikon MRconfocal microscope. Images were processed using NIS Elements or ImageJ(Rasband 1997-2012, Image J, U.S. National Institutes of Health,Bethesda, Md., USA, available at imagej.nih.gov/ij/on the World WideWeb); Schneider et al., Nat Meth 9(7):671-675. (2012)). Some z-stackswere aligned using the “Align Current ND Document” (NIS Elements) or theStackReg plugin (ImageJ) before creating maximum projection images.

Phagocytosis by Microglia/Macrophage Precursors.

Aliquots of zymosan A S. cerevisiae BioParticles® (Texas Red® conjugate;Life Technologies) were prepared in PBS. 5×106 particles in 500 μL PBSwere added to each well of a 6-well plate containing ˜400-500Kmicroglia/macrophage precursors in DM5 media. Phagocytosis was imagedover a 24 hour time period (image capture every 10 minutes) using aNikon Biostation CT.

Flow Cytometry (FACS) Analysis:

Flow cytometry analysis was performed on a BD Biosciences FACSCanto IIcell analyzer.

Neural Progenitor Cells (NPCs).

NPCs were dissociated into single cells with Accutase and fixed with 2%paraformaldehyde in PBS at RT for 10 minutes. Fixed cells were washedonce with FACS buffer I (2% FBS in PBS) and permeabilized with ice cold90% methanol in PBS overnight at −20° C. Fixed and permeabilized cellswere then washed once with FACS buffer I and stained with SOX1 (1:100rabbit anti-SOX1, Cell Signaling) and βIII-tubulin (1:200 mouseanti-βIII-tubulin, R&D systems) primary antibodies overnight at 4° C.followed by conjugated secondary antibodies at RT for one hour. Stainedcells were washed once with FACS buffer I and analyzed by flowcytometry.

Endothelial Cells (ECs).

ECs were dissociated into single cells with Accutase and washed oncewith FACS buffer I (2% FBS in PBS). Cells were stained with PE-CD31(1:100; BD Biosciences, 555446) and APC-CD34 (1:100; BD Biosciences,555824) antibodies in FACS buffer I at 4° C. for 30 minutes. Stainedcells were washed once with FACS buffer I and analyzed by flowcytometry.

Mesenchymal Stem Cells (MSCs).

MSCs were dissociated into single cells with Accutase and washed oncewith FACS buffer I (2% FBS in PBS). Cells were then stained withfluorescently conjugated PE-PDGFR-β and PE-Cy7-CD13 antibodies in FACSbuffer I at 4° C. for 30 minutes. Stained cells were then wash once withFACS buffer I and analyzed by flow cytometry.

Microglia/Macrophage Precursors (MG).

Non-adherent cells were first transferred to a conical vial in DM5medium. Adherent MG were incubated in Accutase, gently removed from theplate using FACS buffer II (0.5% BSA in PBS), and added to the conicalvial containing non-adherent cells. The cells were centrifuged (5minutes at 300×g) and the cell pellet was washed once with FACS bufferII. Cells were then centrifuged (5 minutes at 300×g), resuspended inFACS buffer II, and incubated at 4° C. for 15 minutes for blocking.Cells were centrifuged (5 minutes at 300×g) and resuspended in FACSbuffer II with 1:500 PE-CD11b (BD Biosciences, 555388), Alexa Fluor488-CD14 (BD Biosciences, 562689) and APC-CD45 (BD Biosciences, 555485)and then incubated at 4° C. for 30 minutes (use a shaker plate or inverttube at least three times during incubation). Cells were then washedtwice in FACS buffer II and centrifuged (5 minutes at 300×g). Finally,cells were resuspended in FACS buffer II and analyzed by flow cytometry.

Example 3 Predictive Developmental Neurotoxicity Screening In Vitro

For toxicity screening experiments, cells were seeded as described above(Examples 1 and 2), but with 65,000 cells/well for ECs+MSCs (also 5:1ratio) and 15,000 cells/well for microglia/macrophage precursors. Neuralconstructs were treated with non-toxic or toxic compounds starting atday 14, with media exchanged every 2 days. See FIG. 8. The followingscreening protocol was developed by the Thomson lab. Toxic chemicals(FIG. 10E) were chosen based on previous literature support forneurotoxicity (Adams et al., Neurotoxicol Teratol 15(3):193-202 (1993);Cooper et al., Science 280(5369):1603-1607 (1998); Crofton et al.,ALTEX-Altern Anim Exp 28(1):9-15 (2011); Eskes et al. (2003); Grandjeanet al., Lancet Neurol. 13:330 (2014); Lidsky (2003); Radio et al.,Neurotoxicol Teratol 32(1):25-35 (2010); Zurich (2002)). The screenincluded the following experimental groups (FIG. 8): (1) construct withneural progenitor cells (NPCs), endothelial cells (ECs), mesenchymalcells (MCs), and primitive macrophages (PMs); (2) construct lackingprimitive macrophages (quality control); (3) neural progenitor cellsonly (quality control).

RNA Isolation, cDNA Library Preparation, and Next Generation Sequencing:

The 3D neuronal constructs were lysed directly in the insert by theaddition of RLT lysis buffer (Qiagen) and stored at −80° C. until beingused for RNA isolation. When total RNA was ready to be extracted, thesamples were thawed and 150 μl of the cell lysates in buffer RLT weretransferred and re-arrayed to a S-block (Qiagen, Cat. No. 19585) to bemixed with 1 volume of 70% ethanol (the rest of the lysates were storedin the −80° C.). Total RNA was then isolated using Qiagen's RNeasy™ 96kit beginning with step 3 of the manufacturer's protocol (RNeasy 96Handbook 01/2002, Using Spin Technology) and included the optional DNasetreatment.

Quality Control Studies:

Samples used for quality control were prepared for RNAseq withIllumina's TruSeq™ RNA Sample Preparation Kit v2 following theLow-Throughput (LT) protocol (TruSeq™ RNA Sample Preparation Guide, Part#15008136, Rev. A) using 100 ng of total RNA as input. The cDNAlibraries were pooled and run on Illumina's HiSeg™ 2500 with a singleread of 51 bp and index read of 7 bp. FASTQ files were generated byCASAVA (v1.8.2). Reads were mapped to the human transcriptome (RefGenev1.1.17) using Bowtie (Langmead et al., Genome Biol 10(3):R25 (2009))(v0.12.8) allowing 2-mismatches and a maximum of 20 multiple hits. Thegene expression values (Transcript per Million Reads or TPM) werecalculated by RSEM (Li et al., BMC Bioinformatics 12:323 (2011))(v1.2.3).

Toxicity Screening Study:

For cDNA preparation for the toxicity screening experiments, mRNA isisolated from purified 100 ng total RNA using Oligo-dT beads (NEB).Isolated mRNA is fragmented in reverse transcription buffer at 85° C.for 7 minutes, and then reverse transcribed with SmartScribe™ reversetranscriptase (Clontech) at 23° C. for 10 minutes followed by a 30minute incubation at 42° C. with a random hexamer oligo:5′-CCTTGGCACCCGAGAATTCCA-3′ (SEQ ID NO:3).

After reverse transcription, RNA is removed by RNaseA and RNaseHtreatment. A partial Illumina 5′ adaptor(/5phos/AGATCGGAAGAGCGTCGTGTAGGGAAAGAGTGTddC) (SEQ ID NO:4) was thenligated to the single stranded cDNA using RNA ligase 1(NEB) overnight at22° C. After purification, ligated cDNA was amplified by 18 cycles ofPCR using oligos that contain full Illumina adaptors(5′-AATGATACGGCGACCACCGAGATCTACACTCTTTCCCTACACGACGCTCTTCCGAT CT-3; SEQID NO:5) and index primer(5′-CAAGCAGAAGACGGCATACGAGATnnnnnnnnnnGTGACTGGAGTTCCTTGGCACCCGAGAATTCCA-3′ (SEQ ID NO:6); nnnnnnnnnn indicates index nucleotides).The indexed cDNA libraries were pooled and sequenced on an IlluminaHiSeq2500 with a single 51 bp read and a 10 bp index read.

RNA-Seq Data Analysis:

RSEM expected read counts for each gene were determined by mediannormalization (utilizing the median normalization function within EBSeq—version 1.5.3) (Leng et al., Bioinformatics 29(8):1035-1043 (2013)).EB-Seq (version 1.5.3) was used to calculate FDR for differentiallyexpressed genes (Leng et al., Bioinformatics 29(8):1035-1043 (2013)).

Gene Ontology Analysis:

Gene ontology (GO) terms were identified using the Database forAnnotation, Visualization and Integrated Discovery (DAVID) (v6.7)functional annotation database (Ashburner et al., Nature Genet25(1):25-29 (2000); Huang et al., Nat Protocols 4(1):44-57 (2008)). GOterms were identified by analyzing differentially expressed genes with(FDR≦0.005) and >3-fold upregulated expression for 3D neural constructsrelative to H1 ES cells (see Table 3). The following settings were usedfor DAVID analysis using differentially expressed genes: Gene_Ontologycategory GOTERM_BP_5; Benjamini corrected p-value ≦0.05; Thresholdoptions: Counts=10, EASE=0.05. GO terms were also identified genes withaverage TPM>16 (N=4, Controls from toxicity experiment) (Dataset S5),which were compared to a combined list of neural, vascular, and glialterms to reduce the total number of genes below 3000 for input intoDAVID (combined list and associated GO categories provided in DatasetS7).

Comparisons to Allen Brain Atlas Data:

Pairwise Spearman rank correlation was calculated for neural constructs(days 16 and 21, toxicity experiment, N=4), H1 ES cells (N=4), and AllenBrain Atlas data (RNA-seq data only, samples: 8 pcw—40 yrs) (Table 3).Hierarchical clustering is performed by average linkage clustering onthose correlations and the distance is 1 minus Spearman correlation.

Machine-Based Learning:

We employed linear support vector machines (SVMs) to construct ourpredictive models (Cortes & Vapnik, Mach Learn 20(3):273-297 (1995);Hardin et al., Stat Appl Genet Mol Biol 3(1):e10 (2004); Struyf et al.,BMC Genomics 9:531 (2008); Vapnik V N (1998) Statistical Learning Theory(Wiley, New York)), which were described in detail previously (Hardin etal., Stat Appl Genet Mol Biol 3(1):e10 (2004); Struyf et al., BMCGenomics 9:531 (2008)). We employed SVMs for the following taskspecification: Given: RNAseq gene expression measurements for roughly19K genes on one day or on several different days following exposure tovarious drugs, together with a neural toxicity label on each drug. Do:Construct a model that, from the same type of expression data on a newdrug, can accurately identify if the drug is neural toxic.

Evaluations of the approach, including estimates of accuracy andreceiver operating characteristic (ROC) curves, were all by hold-outtesting, either leave-one-out cross-validation or use of a blinded trialwith a single hold-out set (Hardin et al., Stat Appl Genet Mol Biol3(1):e10 (2004); Struyf et al., BMC Genomics 9:531 (2008)). A2-dimensional linear support vector machine (SVM) is illustrated in theplot shown in FIG. 10A, where the hyper-plane reduces to a line thatseparates the classes (circles) and maximizes the closest points betweenclasses (the support vectors that fix the position and orientation ofthe hyper-plane). The x_(i)s are the example (circles; genes for thecurrent study), the y_(i)s are their labels (filled or open; toxic ornon-toxic for the current study), and w is the weight vector, or vectorof coefficients on the features (the dimensions). The red portions inthe equation are the additions made for the soft margin version of theSVM (Cortes & Vapnik, Mach Learn 20(3):273-297 (1995)), which minimizesthe incorrectly classified data points in addition to the margin(d_(i)). The linear SVM's output is the weight vector w and the othercoefficient b. To make a prediction, the SVM outputs the numberw′x_(i)−b, and outputs the label 0 (non-toxic, for our applications) ifthis number is less than 0, and 1 otherwise. While the numerical outputdoes not have a probabilistic interpretation as does the output oflogistic regression, it is common to build a logistic regression modelwith one input variable (the SVM's output) from the same training set tooutput a probability (probability of toxic), which we do here.

Leave-One-Out Cross-Validation:

Using the leave-one-out cross-validation methodology, we can compute thenumbers of true positive (toxic) predictions (TP), as well as falsepositive (FP), true negative (non-toxic, TN), and false negativepredictions (FN). From these we can compute accuracy (fraction ofpredictions that are correct) as well as the following: Sensitivity(true positive rate, or recall; TP/(TP+FN)), specificity (TN/(TN+FP)),and precision (or positive predictive value; TP/(TP+FP)), as well asother metrics such as F-measure and negative predictive value.Nevertheless, all of these metrics depend on not only the model thatproduces probabilistic predictions for toxicity but also the probabilitythreshold at which we make positive predictions, such as 0.5. Hence itis common in machine learning and statistical classification to report“thresholdless” curves and or metrics, the most popular being thereceiver operating characteristic (ROC) curve and the area under thiscurve (AUC) such as shown for averaged day 2 and 7 set (FIGS. 9C-9D).The ROC curve plots true positive rate on the y-axis against the falsepositive rate (1-specificity) on the x-axis as the threshold is varied(shown for averaged training set). Random uniform guessing produces adiagonal from lower left to upper right corner and AUC of 0.5, whileperfect prediction produces a graph that goes up to the upper leftcorner and then across and AUC of 1.0.

For leave-one-out cross validation, there were 60 compounds in thetraining set and the method proceeds in 60 steps (FIG. 10E). In eachstep a different data point is held out of the training set, the SVM istrained on the remaining data points, and then it makes its predictionon the held-aside data point. Hence every data point is a test caseexactly once, for a model trained without that data point. Results areaggregated over all the folds, or test cases, to estimate how well theSVM model trained on all the data will perform on a new data point(compound). Predictions were made for both replicates for a testingcompound and averaged together to generate the final ROC. The AUCs forthe training compounds were 0.91 on day 16, 0.88 on day 21, and 0.93 fordata averaged from both days. Thus, the SVM for averaged data from days16 and 21 produced an estimate for future data of 0.93.

Blinded Trial:

In addition to constructing an SVM model, we also aimed to estimate howwell the model predicts the developmental neural toxicities of othercompounds. Merely reporting its accuracy on the training set would beoverly-optimistic. An unbiased “hold-out testing” method was used topredict toxicity for a RNA-seq data set of ten blinded compounds thatwere not in the training set (5 toxins, 5 non-toxic controls) but whoseneural toxicities were known. After construction and optimization usingthe training set, the predictive model was then tested on the unknownsamples.

As a blinded trial, the assignment of toxins was unknown to researchersgenerating the SVM model until after the predictions were made. The SVMfor averaged day 16 and 21 data was chosen to generate predictive genesfrom the training set. The SVM produced probabilities which were used torank the blinded compounds from most likely to least likely toxic, whichwas then used to produce an ROC curve and compute an AUC (“area underthe curve”). In addition, we used a threshold of 0.5 to make definitivepredictions, assigning every molecule with probability ≦0.5 as “control”and all others “toxic.” The AUC generated for the ranking of the blindedset was 0.92, and all compounds except oleic acid were properly assignedas toxic or non-toxic based on the 0.5 probability cutoff. The onlyerror in the ranking was for oleic acid, which was assigned a higherprobability of being toxic than L-741,626 and Ouabain. The accuracy ofthe blinded prediction was 0.9 (9/10 compounds correctly classified),with the only error being the prediction of oleic acid (a control) as aneurotoxin (i.e., a false positive).

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TABLE 3 Averaged Expression Data for Markers of Vascular, Neuronal, andGlial Cell Types NPCs, ECs, MCs NPCs, ECs, MCs NPCs NPCs, ECs, MCs w/owith w/o with ONLY w/PM PMs PMs PMs PMs (Control) Day Day 16 Day 21 Day14 Day 21 Gene.ID 3D Tox Experiment QC Experiment GAPDH 3678.1 4299.37431.1 8239.2 5675.7 5720.6 6737.1 Glial GFAP 149.4 131.9 100.6 173.6143.5 161.5 48.9 S100B 259.7 161.5 201.5 281.3 139.2 212.3 99.4 CD44179.9 299.2 228.5 210.7 285.3 314.5 317.3 SLC1A3 (GLAST; Astrocytes,Bergman Glia) 635.4 455.0 315.2 294.2 339.1 369.8 274.5 PDGFRA 3.7 2.87.1 4.1 2.5 3.3 1.2 CLDN11 3.0 3.1 9.0 12.2 4.9 5.8 9.3 MAL 5.1 3.3 12.819.4 6.4 8.3 11.7 MBP 3.5 4.2 1.2 2.1 2.2 2.5 1.6 DLL1 28.7 19.5 38.819.4 28.5 23.2 17.5 FOXM1 17.8 13.5 39.9 42.1 27.3 27.3 11.0 TMPO 138.777.9 59.1 67.1 52.1 63.0 49.0 Microglia AIF1 (IBA1) 12.1 15.6 0.3 17.30.0 10.2 0.0 ITGAM (Cd11b) 2.3 1.2 0.0 0.5 0.0 0.9 0.0 PTPRC (CD45) 4.13.6 0.1 2.6 0.1 1.1 0.0 CD68 17.3 23.8 6.4 32.7 6.4 23.1 7.8 CD86 3.62.9 0.0 4.2 0.0 1.6 0.0 CD14 1.8 3.0 0.0 21.4 0.5 7.3 0.4 CD4 3.8 3.22.0 12.4 2.1 4.8 0.9 TREM2 (Resting MG, strong cortex) 6.7 7.0 0.0 7.90.0 3.8 0.0 Neural General MAP2 779.9 684.3 271.6 205.3 293.3 268.5310.8 CDH2 777.6 665.9 338.8 256.8 300.1 298.9 235.5 ACHE 22.6 20.2 32.036.6 52.4 57.0 50.9 SLC18A3 (vesicular acetylcholine transporter) 1.91.7 0.9 0.7 1.3 0.8 1.1 TPH1 1.0 0.4 1.0 0.5 0.4 0.7 0.8 TH 5.5 5.8 10.814.7 12.9 10.9 16.8 NEUROG2 (Ngn2) 71.7 55.6 84.7 64.5 51.8 62.4 78.9ISL1 5.9 3.3 2.0 2.4 3.5 4.6 5.0 GABAergic GAD1 11.5 31.6 12.7 7.0 22.117.3 28.9 GAD2 1.8 2.9 2.3 3.0 3.7 4.2 4.5 SLC6A1 (GABA transporter 1)9.8 12.5 5.2 2.8 13.4 10.4 9.2 CALB2 (CalRet) 111.7 156.4 171.3 147.8214.9 219.4 204.9 ASCL1 (MASH1) 20.8 14.3 31.4 10.1 26.6 15.5 11.3Glutamatergic SLC32A1 (VGAT) 1.0 2.0 0.6 0.5 0.7 1.0 1.0 GLUL(glutamate-ammonia ligase) 137.7 285.3 95.4 117.7 154.2 170.2 229.7SLC17A7 (VGLUT1) 0.6 0.8 1.4 1.1 3.4 2.2 3.9 SLC17A6 (VGLUT2) 93.5 110.048.0 35.9 85.8 74.9 95.9 SLC17A8 (VGLUT3) 10.6 14.7 6.9 5.5 9.0 8.1 5.1SLC1A1 (glial high affinity glutamate transporter) 4.9 7.0 4.3 2.2 4.83.8 3.4 SLC1A2(neuronal/epithelial high affinity glutamate 103.2 93.437.1 31.6 52.0 33.7 39.9 transporter) Transporter and Vesicle proteinsSV2A 90.9 77.1 92.3 96.7 115.3 105.1 122.9 SV2B 2.2 3.4 1.1 1.0 3.4 2.32.7 SV2C 10.5 4.1 2.4 1.7 3.3 2.5 1.6 SNAP25 95.3 112.3 65.7 56.3 96.298.4 117.6 CBLN1 (Cerebellin-1) 34.7 36.7 24.0 21.7 38.5 39.9 40.9 CBLN214.2 13.9 7.0 7.5 8.3 6.8 7.5 CBLN3 1.2 1.3 2.3 2.6 2.3 2.9 3.3 CBLN46.1 6.5 1.8 1.1 3.9 2.3 3.3 DLG4 (PSD-95) 101.2 140.7 118.4 85.2 168.7150.3 165.6 SYP (synaptophysin) 44.6 54.6 64.0 63.5 100.9 112.0 113.2SYN1 (synapsin I) 26.6 32.4 22.9 23.7 42.7 53.2 46.0 SYN2 7.5 14.1 3.63.4 9.7 8.7 8.0 SYN3 3.3 5.9 4.4 1.5 10.7 12.3 10.1 Blood Vessel (EC orMC) PECAM1/CD31 1.4 1.7 2.1 4.1 1.4 2.1 1.0 CD34 22.8 12.7 40.9 70.918.1 31.5 28.0 MCAM 15.7 23.8 36.9 33.9 39.0 42.0 51.1 KDR/VEGFR2/FLK19.2 8.7 13.0 25.8 7.8 11.5 11.4 VEGFA 512.8 890.2 623.5 294.7 677.6829.1 732.8 PDGFRB 10.5 12.1 40.2 30.4 37.2 32.2 15.6 PDGFB 24.8 14.232.7 41.4 20.9 21.9 30.0 ANPEP 2.1 1.5 3.6 7.1 2.1 3.8 2.4 CSPG4 1.9 1.711.9 12.1 12.3 10.8 8.8 ACTA2 30.8 88.9 254.4 181.2 168.2 240.3 143.4CDH5 2.0 0.3 4.5 5.0 1.9 2.6 1.1 SLC2A1 95.0 139.6 262.0 66.2 129.7 98.3133.7 AQP1 5.1 9.5 11.6 18.6 17.1 25.5 6.6 GPR124 1.2 1.2 17.8 13.0 6.78.6 1.5 AQP4 64.6 52.8 29.5 31.2 32.3 29.4 39.4 NPC NES 1275.2 763.9620.7 895.9 562.5 642.7 625.1 VIM 5871.3 8872.8 13171.0 9312.2 15142.813388.9 14840.7 EOMES/Tbr2 1.6 2.2 3.5 3.3 3.1 3.7 4.3 PAX6 3.7 2.6 1.71.6 1.9 2.2 2.0 SOX1 75.2 53.9 34.4 40.6 33.2 40.1 22.4 SOX2 138.5 160.7247.4 184.8 249.3 341.0 202.7 SOX9 169.3 153.2 106.7 62.9 110.9 133.687.6 NEUROD1 14.0 16.6 7.6 5.5 6.1 9.1 11.9 NOTCH1 82.7 81.0 153.2 95.9173.7 129.0 128.1 NOTCH2 51.1 40.7 46.6 38.1 53.9 40.8 45.4 NR2F1(COUP-TF1) 51.9 48.6 40.1 35.9 42.5 43.4 32.5 Cortical RELN 72.9 45.158.3 35.6 50.6 31.4 44.7 CUX1 54.0 54.0 57.7 46.1 60.0 65.6 52.9 CUX218.7 14.6 23.0 21.1 26.4 27.9 26.3 SATB1 72.5 56.5 43.7 24.3 49.0 49.141.3 SATB2 10.1 8.3 7.6 7.1 7.7 8.0 8.2 RORB 3.0 1.9 1.5 0.7 3.1 2.3 1.3BCL11B/Ctip2 37.4 34.1 11.5 8.5 12.4 9.0 11.4 SOX5 13.5 5.9 9.9 5.3 8.37.1 6.7 POU3F1/SCIP 7.4 6.5 7.9 10.1 7.1 8.9 7.4 FOXP1 30.1 29.6 22.819.5 16.8 18.4 15.7 FOXP2 34.5 27.3 33.7 19.2 25.2 32.7 24.1 ETV1 19.118.2 11.4 7.1 10.4 11.6 9.5 MAP1B 1001.4 782.1 460.8 349.1 454.6 375.1429.3 TLE4 43.3 48.4 47.6 33.0 37.2 36.8 44.9 POU3F2/Brn2 160.9 122.6118.0 82.3 122.6 121.2 96.5 FOXO1 1.6 2.0 4.3 2.6 2.5 1.9 2.3 LIX1 5.13.9 4.7 2.9 6.5 3.9 3.7 SYT9 35.7 22.5 19.9 17.0 25.0 25.8 18.9 S100A10117.2 124.3 344.4 458.2 215.5 308.7 268.4 OMA1 11.3 14.8 9.8 6.9 11.610.5 9.0 LDB2 33.0 39.3 37.0 22.1 38.4 44.1 33.0 CRIM1 42.6 36.7 32.523.8 27.8 24.6 29.5 PCP4 5.5 8.3 5.2 3.3 11.0 9.7 12.6 RAC3 52.7 60.9133.5 158.5 152.2 166.3 169.2 CRYM 4.2 4.9 2.7 3.1 1.3 2.3 3.2 IGFBP410.5 17.8 54.6 50.9 42.2 48.2 28.7 DKK3 409.7 388.8 1003.0 803.8 1185.81219.9 752.7 SEMA3E 3.6 3.5 4.4 3.6 2.6 3.0 2.9 NR4A3 3.5 2.7 1.3 0.81.1 1.6 1.4 LXN 4.5 1.8 14.2 13.9 7.4 12.2 2.2 ID2 120.1 227.6 242.1115.5 202.2 188.7 132.2 SLITRK1 12.6 14.7 5.4 6.2 5.2 5.4 6.6 LMO3 5.66.8 2.0 1.2 4.0 3.0 3.5 LMO4 73.0 101.2 65.5 56.9 100.2 78.7 101.1 CTGF127.1 112.5 330.6 173.2 123.6 95.9 143.8 Ependyma/Neuroepithelium(early) PROM1 (CD133) 92.7 97.9 55.8 47.5 70.0 68.0 47.6 ITGA6 77.1 56.326.6 22.6 23.0 20.7 30.8 NPC = neural progenitor cells; ECs =endothelial cells; MCs = mesenchymal cells; PM = primitive macrophages

We claim:
 1. A method of producing a vascularized neural tissueconstruct, comprising (a) seeding a three-dimensional porous biomaterialwith human neural progenitor cells; (b) culturing the seeded biomaterialfor a length of time sufficient to detect differentiation of at least aportion of the neural progenitor cells; (c) dispersing on or within thecultured seeded biomaterial human endothelial cells and, optionally, oneor more of human mesenchymal cells, primitive macrophages, andpericytes; and (d) culturing the seeded biomaterial comprising thedispersed human endothelial cells under culture conditions that promotecell differentiation, whereby a vascularized neural tissue constructcomprising human neurons and glial cells is produced.
 2. The method ofclaim 1, wherein the three-dimensional porous biomaterial is a hydrogel.3. The method of claim 2, wherein the hydrogel comprises polymerizedpoly(ethylene glycol) (PEG) or polymerized polysaccharide.
 4. The methodof claim 1, wherein the dispersed human endothelial cells are derivedfrom a human pluripotent stem cell.
 5. The method of claim 4, whereinthe human pluripotent stem cell is an embryonic stem cell or an inducedpluripotent stem cell.
 6. The method of claim 1, wherein the seededbiomaterial comprising the dispersed human endothelial cells furthercomprises human pluripotent stem cell-derived primitive macrophages andwherein the 3D vascularized neural tissue construct comprises maturemicroglia.
 7. The method of claim 1, wherein seeding the porousbiomaterial comprises contacting to the porous biomaterial at least onehuman neural progenitor cell.
 8. The method of claim 1, furthercomprising dispersing within or on the porous biomaterial a bioactiveagent that modulates a morphological feature, function, ordifferentiation status of a cell seeded or dispersed therein.
 9. Themethod of claim 8, wherein the bioactive agent is selected from thegroup consisting of a growth factor, a cytokine, and a bioactivepeptide, or a combination thereof.
 10. The method of claim 1, whereinthe vascularized neural tissue construct exhibits one or more propertiesselected from the group consisting of: (i) an interconnectedvasculature; (ii) differentiated cells within the neural tissueconstruct mutually contact each other in three dimensions; (iii) morethan one layer of cells; and (iv) a function or property characteristicof human neural tissue in vivo or in situ.
 11. The method of claim 1,wherein the neurons and glial cells are selected from the groupconsisting of GABAergic neurons, giutamatergic neurons, astrocytes, andoligodendrocytes.
 12. The method of claim 1, wherein the porousbiomaterial is degradable.
 13. The method of claim 12, wherein thedegradable porous biomaterial is selected from the group consisting ofan enzymatically degradable hydrogel, a hydrolytically degradablehydrogel, or a photodegradable hydrogel.
 14. The method of claim 13,wherein the enzymatically degradable hydrogel is matrixmetalloproteinase (MMP)-degradable.
 15. A three-dimensional (3D)vascularized neural tissue construct obtained according to the method ofclaim
 1. 16. The neural tissue construct of claim 15, comprising maturemicroglia.
 17. The neural tissue construct of claim 15, comprisingstratified layers of neurons and glia.
 18. A method of in vitroscreening of an agent, comprising (a) contacting a test agent to avascularized neural tissue construct obtained according to the method ofclaim 1; and (b) detecting an effect of the agent on one or more celltypes within the contacted neural tissue construct.
 19. The method ofclaim 18, wherein the agent is screened for toxicity to human neuraltissue.
 20. The method of claim 18, wherein detecting comprisesdetecting at least one effect of the agent on morphology or life span ofcells or tissues within the contacted tissue construct, whereby an agentthat reduces the life span of the cells or tissues or has a negativeimpact on the morphology of the cells or tissues is identified as toxicto human neural tissue.
 21. The method of claim 18, wherein detectingcomprises performing a method selected from the group consisting of RNAsequencing, gene expression profiling, transcriptome analysis,metabolome analysis, detecting reporter or sensor, protein expressionprofiling, Førster resonance energy transfer (FRET), metabolicprofiling, and microdialysis.
 22. The method of claim 18, wherein theagent is screened for an effect on gene expression and wherein detectingcomprises assaying for differential gene expression relative to anuncontacted tissue construct.
 23. The method of claim 18, furthercomprising using a predictive model to determine the relationship ofgene expression levels of a panel of markers for the testcompound-contacted tissue construct to gene expression levels of markersthat are characteristic of exposure to a neurotoxic agent, wherein thepredictive model is constructed using transcription and metabolicprofiles obtained for each component of a panel of agents having knownneurotoxic effects as markers of toxicity to human neural tissue.
 24. Atissue construct screening system, comprising an analytical deviceconfigured to obtain data comprising measurements from a humanvascularized neural tissue construct; a computer controller configuredto receive the data from the analytical device; and a machine-basedadaptive learning system trained using known gene expression data andconfigured to select a subset of features from the data using a featureselection algorithm, wherein the subset of features correspond to achange in a level of expression of at least one gene following exposureto a known or unknown compound.
 25. The system of claim 24, wherein thehuman vascularized neural tissue construct is obtained according to themethod of claim
 1. 26. The system of claim 24, wherein the measurementscomprise gene expression data obtained from microarray analysis.